Papers archive | Social & Information Systems

Informativeness of Reward Functions in Reinforcement Learning.

Rati Devidze, Parameswaran Kamalaruban, Adish Singla.
AAMAS 2024.

Speech language models lack important brain-relevant semantics.

Subba Reddy Oota, Emin Çelik, Fatma Deniz, Mariya Toneva.
ACL 2024.

Perturbed examples reveal invariances shared by language models.

Ruchit Rawal, Mariya Toneva.
ACL (Findings) 2024.

Task Synthesis for Elementary Visual Programming in XLogoOnline Environment.

Chao Wen, Ahana Ghosh, Jacqueline Staub, Adish Singla.
AIED Companion 2024.

Corruption-Robust Offline Two-Player Zero-Sum Markov Games.

Andi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic.
AISTATS 2024.

Analyzing User Engagement with TikTok's Short Format Video Recommendations using Data Donations.

Savvas Zannettou, Olivia Nemes Nemeth, Oshrat Ayalon, Angelica Goetzen, Krishna P. Gummadi, Elissa M. Redmiles, Franziska Roesner.
CHI 2024.

Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming.

Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla.
EDM 2024.

Leveraging Large Language Models for Next-Generation Educational Technologies.

Neil T. Heffernan, Rose Wang, Christopher MacLellan, Arto Hellas, Chenglu Li, Candace Walkington, Joshua Littenberg-Tobias, David Joyner, Steven Moore, Adish Singla, Zach Pardos, Maciej Pankiewicz, Juho Kim, Shashank Sonkar, Clayton Cohn, Anthony Botelho, Andrew Lan, Lan Jiang, Mingyu Feng, Tanja Käser, Eamon Worden.
EDM 2024.

Towards Generalizable Agents in Text-Based Educational Environments: A Study of Integrating RL with LLMs.

Bahar Radmehr, Adish Singla, Tanja Käser.
EDM 2024.

Language models and brains align due to more than next-word prediction and word-level information.

Gabriele Merlin, Mariya Toneva.
EMNLP 2024.

Designing Decision Support Systems using Counterfactual Prediction Sets.

Eleni Straitouri, Manuel Gomez Rodriguez.
ICML 2024.

Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences.

Andi Nika, Debmalya Mandal, Parameswaran Kamalaruban, Georgios Tzannetos, Goran Radanovic, Adish Singla.
ICML 2024.

Auditing Algorithmic Explanations of Social Media Feeds: A Case Study of TikTok Video Explanations.

Sepehr Mousavi, Krishna P. Gummadi, Savvas Zannettou.
ICWSM 2024.

Learning Embeddings for Sequential Tasks Using Population of Agents.

Mridul Mahajan, Georgios Tzannetos, Goran Radanovic, Adish Singla.
IJCAI 2024.

Proximal Curriculum with Task Correlations for Deep Reinforcement Learning.

Georgios Tzannetos, Parameswaran Kamalaruban, Adish Singla.
IJCAI 2024.

Automating Human Tutor-Style Programming Feedback: Leveraging GPT-4 Tutor Model for Hint Generation and GPT-3.5 Student Model for Hint Validation.

Tung Phung, Victor-Alexandru Padurean, Anjali Singh, Christopher Brooks, José Cambronero, Sumit Gulwani, Adish Singla, Gustavo Soares.
LAK 2024.

(De)Noise: Moderating the Inconsistency Between Human Decision-Makers.

Nina Grgic-Hlaca, Junaid Ali, Krishna P. Gummadi, Jennifer Wortman Vaughan.
Proc. ACM Hum. Comput. Interact. 2024.

Investigating Nudges toward Related Sellers on E-commerce Marketplaces: A Case Study on Amazon.

Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh, Animesh Mukherjee, Krishna P. Gummadi.
Proc. ACM Hum. Comput. Interact. 2024.

Analyzing-Evaluating-Creating: Assessing Computational Thinking and Problem Solving in Visual Programming Domains.

Ahana Ghosh, Liina Malva, Adish Singla.
SIGCSE 2024.

Neural Task Synthesis for Visual Programming.

Victor-Alexandru Padurean, Georgios Tzannetos, Adish Singla.
Trans. Mach. Learn. Res. 2024.

Understanding the Role of Invariance in Transfer Learning.

Till Speicher, Vedant Nanda, Krishna P. Gummadi.
Trans. Mach. Learn. Res. 2024.

Coupling GDPR Data Donation and Crowdsourced User Survey: A Case Study on TikTok Addiction.

Cai Yang, Sepehr Mousavi, Abhisek Dash, Krishna P. Gummadi, Ingmar Weber.
WebSci 2024.

TikTok and the Art of Personalization: Investigating Exploration and Exploitation on Social Media Feeds.

Karan Vombatkere, Sepehr Mousavi, Savvas Zannettou, Franziska Roesner, Krishna P. Gummadi.
WWW 2024.

Do Invariances in Deep Neural Networks Align with Human Perception?

Vedant Nanda, Ayan Majumdar, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Bradley C. Love, Adrian Weller.
AAAI 2023.

Online Reinforcement Learning with Uncertain Episode Lengths.

Debmalya Mandal, Goran Radanovic, Jiarui Gan, Adish Singla, Rupak Majumdar.
AAAI 2023.

Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks.

Mohammad Mohammadi, Jonathan Nöther, Debmalya Mandal, Adish Singla, Goran Radanovic.
AAMAS 2023.

Online Defense Strategies for Reinforcement Learning Against Adaptive Reward Poisoning.

Andi Nika, Adish Singla, Goran Radanovic.
AISTATS 2023.

"Nudes? Shouldn't I charge for these?": Motivations of New Sexual Content Creators on OnlyFans.

Vaughn Hamilton, Ananta Soneji, Allison McDonald, Elissa M. Redmiles.
CHI 2023.

What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation.

Gabriele Merlin, Vedant Nanda, Ruchit Rawal, Mariya Toneva.
CoLLAs 2023.

Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models.

Tung Phung, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla, Gustavo Soares.
EDM 2023.

Dissecting Bitcoin and Ethereum Transactions: On the Lack of Transaction Contention and Prioritization Transparency in Blockchains.

Johnnatan Messias, Vabuk Pahari, Balakrishnan Chandrasekaran, Krishna P. Gummadi, Patrick Loiseau.
FC 2023.

Training language models to summarize narratives improves brain alignment.

Khai Loong Aw, Mariya Toneva.
ICLR 2023.

Improving Expert Predictions with Conformal Prediction.

Eleni Straitouri, Lequn Wang, Nastaran Okati, Manuel Gomez Rodriguez.
ICML 2023.

On the Within-Group Fairness of Screening Classifiers.

Nastaran Okati, Stratis Tsirtsis, Manuel Gomez Rodriguez.
ICML 2023.

"Learn the Facts about COVID-19": Analyzing the Use of Warning Labels on TikTok Videos.

Chen Ling, Krishna P. Gummadi, Savvas Zannettou.
ICWSM 2023.

Power in Computer Security and Privacy: A Critical Lens.

Elissa M. Redmiles, Mia M. Bennett, Tadayoshi Kohno.
IEEE Secur. Priv. 2023.

FaiRIR: Mitigating Exposure Bias From Related Item Recommendations in Two-Sided Platforms.

Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh, Animesh Mukherjee, Krishna P. Gummadi.
IEEE Trans. Comput. Soc. Syst. 2023.

On the Fairness of Time-Critical Influence Maximization in Social Networks.

Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla.
IEEE Trans. Knowl. Data Eng. 2023.

Specifying and Testing k-Safety Properties for Machine-Learning Models.

Maria Christakis, Hasan Ferit Eniser, Jörg Hoffmann, Adish Singla, Valentin Wüstholz.
IJCAI 2023.

"I need a better description": An Investigation Into User Expectations For Differential Privacy.

Rachel Cummings, Gabriel Kaptchuk, Elissa M. Redmiles.
J. Priv. Confidentiality 2023.

Responsible model deployment via model-agnostic uncertainty learning.

Preethi Lahoti, P. Krishna Gummadi, Gerhard Weikum.
Mach. Learn. 2023.

Diffused Redundancy in Pre-trained Representations.

Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Soheil Feizi, Adrian Weller.
NeurIPS 2023.

Joint processing of linguistic properties in brains and language models.

Subba Reddy Oota, Manish Gupta, Mariya Toneva.
NeurIPS 2023.

Defense Against Reward Poisoning Attacks in Reinforcement Learning.

Kiarash Banihashem, Adish Singla, Goran Radanovic.
Trans. Mach. Learn. Res. 2023.

Proximal Curriculum for Reinforcement Learning Agents.

Georgios Tzannetos, Bárbara Gomes Ribeiro, Parameswaran Kamalaruban, Adish Singla.
Trans. Mach. Learn. Res. 2023.

Exploring Privacy and Incentives Considerations in Adoption of COVID-19 Contact Tracing Apps.

Oshrat Ayalon, Dana Turjeman, Elissa M. Redmiles.
USENIX Security Symposium 2023.

Problematic Advertising and its Disparate Exposure on Facebook.

Muhammad Ali, Angelica Goetzen, Alan Mislove, Elissa M. Redmiles, Piotr Sapiezynski.
USENIX Security Symposium 2023.

What Are the Chances? Explaining the Epsilon Parameter in Differential Privacy.

Priyanka Nanayakkara, Mary Anne Smart, Rachel Cummings, Gabriel Kaptchuk, Elissa M. Redmiles.
USENIX Security Symposium 2023.

Admissible Policy Teaching through Reward Design.

Kiarash Banihashem, Adish Singla, Jiarui Gan, Goran Radanovic.
AAAI 2022.

Bayesian Persuasion in Sequential Decision-Making.

Jiarui Gan, Rupak Majumdar, Goran Radanovic, Adish Singla.
AAAI 2022.

CrossWalk: Fairness-Enhanced Node Representation Learning.

Ahmad Khajehnejad, Moein Khajehnejad, Mahmoudreza Babaei, Krishna P. Gummadi, Adrian Weller, Baharan Mirzasoleiman.
AAAI 2022.

The Network Visibility Problem.

Khashayar Gatmiry, Manuel Gomez-Rodriguez.
ACM Trans. Inf. Syst. 2022.

Quantifying the Effects of Contact Tracing, Testing, and Containment Measures in the Presence of Infection Hotspots.

Lars Lorch, Heiner Kremer, William Trouleau, Stratis Tsirtsis, Aron Szanto, Bernhard Schölkopf, Manuel Gomez-Rodriguez.
ACM Trans. Spatial Algorithms Syst. 2022.

Toward Fair Recommendation in Two-sided Platforms.

Arpita Biswas, Gourab K. Patro, Niloy Ganguly, Krishna P. Gummadi, Abhijnan Chakraborty.
ACM Trans. Web 2022.

Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes.

Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla.
AIED 2022.

Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes.

Stelios Triantafyllou, Adish Singla, Goran Radanovic.
AIES 2022.

On fair selection in the presence of implicit and differential variance.

Vitalii Emelianov, Nicolas Gast, Krishna P. Gummadi, Patrick Loiseau.
Artif. Intell. 2022.

A Large-Scale Measurement of Cybercrime Against Individuals.

Casey Breen, Cormac Herley, Elissa M. Redmiles.
CHI 2022.

Field Evidence of the Effects of Privacy, Data Transparency, and Pro-social Appeals on COVID-19 App Attractiveness.

Samuel Dooley, Dana Turjeman, John P. Dickerson, Elissa M. Redmiles.
CHI 2022.

COVID-19 Information-Tracking Solutions: A Qualitative Investigation of the Factors Influencing People's Adoption Intention.

Yue Huang, Borke Obada-Obieh, Elissa M. Redmiles, Satya Lokam, Konstantin Beznosov.
CHIIR 2022.

Same Cause; Different Effects in the Brain.

Mariya Toneva, Jennifer Williams, Anand Bollu, Christoph Dann, Leila Wehbe.
CLeaR 2022.

Deep Learning for Brain Encoding and Decoding.

Subba Reddy Oota, Jashn Arora, Manish Gupta, Raju Surampudi Bapi, Mariya Toneva.
CogSci 2022.

Sequential Decision Making With Information Asymmetry (Invited Talk).

Jiarui Gan, Rupak Majumdar, Goran Radanovic, Adish Singla.
CONCUR 2022.

Dimensions of Diversity in Human Perceptions of Algorithmic Fairness.

Nina Grgic-Hlaca, Gabriel Lima, Adrian Weller, Elissa M. Redmiles.
EAAMO 2022.

Equity and Fairness of Bayesian Knowledge Tracing.

Sebastian Tschiatschek, Maria Knobelsdorf, Adish Singla.
EDM 2022.

From Solution Synthesis to Student Attempt Synthesis for Block-Based Visual Programming Tasks.

Adish Singla, Nikitas Theodoropoulos.
EDM 2022.

Ethical Practices for Security Research with At-Risk Populations.

Rasika Bhalerao, Vaughn Hamilton, Allison McDonald, Elissa M. Redmiles, Angelika Strohmayer.
EuroS&P Workshops 2022.

Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making.

Miriam Rateike, Ayan Majumdar, Olga Mineeva, Krishna P. Gummadi, Isabel Valera.
FAccT 2022.

Taking Advice from (Dis)Similar Machines: The Impact of Human-Machine Similarity on Machine-Assisted Decision-Making.

Nina Grgic-Hlaca, Claude Castelluccia, Krishna P. Gummadi.
HCOMP 2022.

On the Fairness of Time-Critical Influence Maximization in Social Networks (Extended Abstract).

Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla.
ICDE 2022.

Evaluating ChatGPT and GPT-4 for Visual Programming.

Adish Singla.
ICER 2022.

Generative AI for Programming Education: Benchmarking ChatGPT, GPT-4, and Human Tutors.

Tung Phung, Victor-Alexandru Padurean, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla, Gustavo Soares.
ICER 2022.

Improving Screening Processes via Calibrated Subset Selection.

Lequn Wang, Thorsten Joachims, Manuel Gomez Rodriguez.
ICML 2022.

Measuring Representational Robustness of Neural Networks Through Shared Invariances.

Vedant Nanda, Till Speicher, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Adrian Weller.
ICML 2022.

Community Under Surveillance: Impacts of Marginalization on an Online Labor Forum.

Hanna Barakat, Elissa M. Redmiles.
ICWSM 2022.

Analyzing Biases in Perception of Truth in News Stories and Their Implications for Fact Checking.

Mahmoudreza Babaei, Juhi Kulshrestha, Abhijnan Chakraborty, Elissa M. Redmiles, Meeyoung Cha, Krishna P. Gummadi.
IEEE Trans. Comput. Soc. Syst. 2022.

Combining computational controls with natural text reveals aspects of meaning composition.

Mariya Toneva, Tom M. Mitchell, Leila Wehbe.
Nat. Comput. Sci. 2022.

Counterfactual Temporal Point Processes.

Kimia Noorbakhsh, Manuel Gomez-Rodriguez.
NeurIPS 2022.

Envy-free Policy Teaching to Multiple Agents.

Jiarui Gan, Rupak Majumdar, Adish Singla, Goran Radanovic.
NeurIPS 2022.

Exploration-Guided Reward Shaping for Reinforcement Learning under Sparse Rewards.

Rati Devidze, Parameswaran Kamalaruban, Adish Singla.
NeurIPS 2022.

On Batch Teaching with Sample Complexity Bounded by VCD.

Farnam Mansouri, Hans Simon, Adish Singla, Sandra Zilles.
NeurIPS 2022.

Provable Defense against Backdoor Policies in Reinforcement Learning.

Shubham Kumar Bharti, Xuezhou Zhang, Adish Singla, Jerry Zhu.
NeurIPS 2022.

The Need for Respectful Technologies: Going Beyond Privacy.

Elissa M. Redmiles.
Perspectives on Digital Humanism 2022.

Pooled testing of traced contacts under superspreading dynamics.

Stratis Tsirtsis, Abir De, Lars Lorch, Manuel Gomez-Rodriguez.
PLoS Comput. Biol. 2022.

Ethics and Efficacy of Unsolicited Anti-Trafficking SMS Outreach.

Rasika Bhalerao, Nora McDonald, Hanna Barakat, Vaughn Hamilton, Damon McCoy, Elissa M. Redmiles.
Proc. ACM Hum. Comput. Interact. 2022.

Risk, Resilience and Reward: Impacts of Shifting to Digital Sex Work.

Vaughn Hamilton, Hanna Barakat, Elissa M. Redmiles.
Proc. ACM Hum. Comput. Interact. 2022.

Not Only for Contact Tracing: Use of Belgium's Contact Tracing App among Young Adults.

Oshrat Ayalon, Sophie Li, Bart Preneel, Elissa M. Redmiles.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2022.

Ctrl-Shift: How Privacy Sentiment Changed from 2019 to 2021.

Angelica Goetzen, Samuel Dooley, Elissa M. Redmiles.
Proc. Priv. Enhancing Technol. 2022.

Learning to Switch Among Agents in a Team.

Vahid Balazadeh Meresht, Abir De, Adish Singla, Manuel Gomez Rodriguez.
Trans. Mach. Learn. Res. 2022.

Counterfactual inference of second Opinions.

Nina L. Corvelo Benz, Manuel Gomez Rodriguez.
UAI 2022.

"Like Lesbians Walking the Perimeter": Experiences of U.S. LGBTQ+ Folks With Online Security, Safety, and Privacy Advice.

Christine Geeng, Mike Harris, Elissa M. Redmiles, Franziska Roesner.
USENIX Security Symposium 2022.

Alexa, in you, I trust! Fairness and Interpretability Issues in E-commerce Search through Smart Speakers.

Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh, Animesh Mukherjee, Krishna P. Gummadi.
WWW 2022.

Scheduling Virtual Conferences Fairly: Achieving Equitable Participant and Speaker Satisfaction.

Gourab K. Patro, Prithwish Jana, Abhijnan Chakraborty, Krishna P. Gummadi, Niloy Ganguly.
WWW 2022.

Classification Under Human Assistance.

Abir De, Nastaran Okati, Ali Zarezade, Manuel Gomez Rodriguez.
AAAI 2021.

The Sample Complexity of Teaching by Reinforcement on Q-Learning.

Xuezhou Zhang, Shubham Kumar Bharti, Yuzhe Ma, Adish Singla, Xiaojin Zhu.
AAAI 2021.

Fair Clustering Using Antidote Data.

Anshuman Chhabra, Adish Singla, Prasant Mohapatra.
AFCR 2021.

Accounting for Model Uncertainty in Algorithmic Discrimination.

Junaid Ali, Preethi Lahoti, Krishna P. Gummadi.
AIES 2021.

Beyond Reasonable Doubt: Improving Fairness in Budget-Constrained Decision Making using Confidence Thresholds.

Michiel A. Bakker, Duy Patrick Tu, Krishna P. Gummadi, Alex 'Sandy' Pentland, Kush R. Varshney, Adrian Weller.
AIES 2021.

The Teaching Dimension of Kernel Perceptron.

Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen.
AISTATS 2021.

"I need a better description": An Investigation Into User Expectations For Differential Privacy.

Rachel Cummings, Gabriel Kaptchuk, Elissa M. Redmiles.
CCS 2021.

An Inside Look into the Practice of Malware Analysis.

Miuyin Yong Wong, Matthew Landen, Manos Antonakakis, Douglas M. Blough, Elissa M. Redmiles, Mustaque Ahamad.
CCS 2021.

"Disadvantaged in the American-dominated Internet": Sex, Work, and Technology.

Catherine Barwulor, Allison McDonald, Eszter Hargittai, Elissa M. Redmiles.
CHI 2021.

Diversity in News Recommendation (Dagstuhl Perspectives Workshop 19482).

Abraham Bernstein, Claes H. de Vreese, Natali Helberger, Wolfgang Schulz, Katharina Anna Zweig, Christian Baden, Michael A. Beam, Marc P. Hauer, Lucien Heitz, Pascal Jürgens, Christian Katzenbach, Benjamin Kille, Beate Klimkiewicz, Wiebke Loosen, Judith Müller, Goran Radanovic, Guy Shani, Nava Tintarev, Suzanne Tolmeijer, Wouter van Atteveldt, Sanne Vrijenhoek, Theresa Zueger.
Dagstuhl Manifestos 2021.

User Concerns 8 Tradeoffs in Technology-facilitated COVID-19 Response.

Elissa M. Redmiles.
Digit. Gov. Res. Pract. 2021.

When the Umpire is also a Player: Bias in Private Label Product Recommendations on E-commerce Marketplaces.

Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh, Animesh Mukherjee, Krishna P. Gummadi.
FAccT 2021.

Single-Trial MEG Data Can Be Denoised Through Cross-Subject Predictive Modeling.

Srinivas Ravishankar, Mariya Toneva, Leila Wehbe.
Frontiers Comput. Neurosci. 2021.

Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning.

Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum.
ICDM 2021.

Selfish & opaque transaction ordering in the Bitcoin blockchain: the case for chain neutrality.

Johnnatan Messias, Mohamed Alzayat, Balakrishnan Chandrasekaran, Krishna P. Gummadi, Patrick Loiseau, Alan Mislove.
IMC 2021.

Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks.

Amin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu, Adish Singla.
J. Mach. Learn. Res. 2021.

AMP: authentication of media via provenance.

Paul England, Henrique S. Malvar, Eric Horvitz, Jack W. Stokes, Cédric Fournet, Rebecca Burke-Aguero, Amaury Chamayou, Sylvan Clebsch, Manuel Costa, John Deutscher, Shabnam Erfani, Matt Gaylor, Andrew Jenks, Kevin Kane, Elissa M. Redmiles, Alex Shamis, Isha Sharma, John C. Simmons, Sam Wenker, Anika Zaman.
MMSys 2021.

Auditing Black-Box Prediction Models for Data Minimization Compliance.

Bashir Rastegarpanah, Krishna P. Gummadi, Mark Crovella.
NeurIPS 2021.

Curriculum Design for Teaching via Demonstrations: Theory and Applications.

Gaurav Yengera, Rati Devidze, Parameswaran Kamalaruban, Adish Singla.
NeurIPS 2021.

Differentiable Learning Under Triage.

Nastaran Okati, Abir De, Manuel Gomez-Rodriguez.
NeurIPS 2021.

Explicable Reward Design for Reinforcement Learning Agents.

Rati Devidze, Goran Radanovic, Parameswaran Kamalaruban, Adish Singla.
NeurIPS 2021.

On Blame Attribution for Accountable Multi-Agent Sequential Decision Making.

Stelios Triantafyllou, Adish Singla, Goran Radanovic.
NeurIPS 2021.

Teaching an Active Learner with Contrastive Examples.

Chaoqi Wang, Adish Singla, Yuxin Chen.
NeurIPS 2021.

Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm.

Akash Kumar, Yuxin Chen, Adish Singla.
NeurIPS 2021.

Characterizing the Online Learning Landscape: What and How People Learn Online.

Sean Kross, Eszter Hargittai, Elissa M. Redmiles.
Proc. ACM Hum. Comput. Interact. 2021.

Designing Media Provenance Indicators to Combat Fake Media.

Imani N. Sherman, Jack W. Stokes, Elissa M. Redmiles.
RAID 2021.

"It's stressful having all these phones": Investigating Sex Workers' Safety Goals, Risks, and Practices Online.

Allison McDonald, Catherine Barwulor, Michelle L. Mazurek, Florian Schaub, Elissa M. Redmiles.
USENIX Security Symposium 2021.

Driving 2FA Adoption at Scale: Optimizing Two-Factor Authentication Notification Design Patterns.

Maximilian Golla, Grant Ho, Marika Lohmus, Monica Pulluri, Elissa M. Redmiles.
USENIX Security Symposium 2021.

From Secure to Military-Grade: Exploring the Effect of App Descriptions on User Perceptions of Secure Messaging.

Omer Akgul, Ruba Abu-Salma, Wei Bai, Elissa M. Redmiles, Michelle L. Mazurek, Blase Ur.
WPES@CCS 2021.

Fair Partitioning of Public Resources: Redrawing District Boundary to Minimize Spatial Inequality in School Funding.

Nuno Mota, Negar Mohammadi, Palash Dey, Krishna P. Gummadi, Abhijnan Chakraborty.
WWW 2021.

Fair Updates in Two-Sided Market Platforms: On Incrementally Updating Recommendations.

Gourab K. Patro, Abhijnan Chakraborty, Niloy Ganguly, Krishna P. Gummadi.
AAAI 2020.

Regression under Human Assistance.

Abir De, Paramita Koley, Niloy Ganguly, Manuel Gomez-Rodriguez.
AAAI 2020.

Minimizing Margin of Victory for Fair Political and Educational Districting.

Ana-Andreea Stoica, Abhijnan Chakraborty, Palash Dey, Krishna P. Gummadi.
AAMAS 2020.

Towards Deployment of Robust Cooperative AI Agents: An Algorithmic Framework for Learning Adaptive Policies.

Ahana Ghosh, Sebastian Tschiatschek, Hamed Mahdavi, Adish Singla.
AAMAS 2020.

Fair Decisions Despite Imperfect Predictions.

Niki Kilbertus, Manuel Gomez Rodriguez, Bernhard Schölkopf, Krikamol Muandet, Isabel Valera.
AISTATS 2020.

How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations.

Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu.
Artif. Intell. 2020.

Fairness in Algorithmic Decision Making.

Abhijnan Chakraborty, Krishna P. Gummadi.
COMAD/CODS 2020.

On Fair Selection in the Presence of Implicit Variance.

Vitalii Emelianov, Nicolas Gast, Krishna P. Gummadi, Patrick Loiseau.
EC 2020.

Zero-shot Learning of Hint Policy via Reinforcement Learning and Program Synthesis.

Aleksandr Efremov, Ahana Ghosh, Adish Singla.
EDM 2020.

Americans' willingness to adopt a COVID-19 tracking app The role of app distributor.

Eszter Hargittai, Elissa M. Redmiles, Jessica Vitak, Michael Zimmer.
First Monday 2020.

Adaptive Reward-Poisoning Attacks against Reinforcement Learning.

Xuezhou Zhang, Yuzhe Ma, Adish Singla, Xiaojin Zhu.
ICML 2020.

Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning.

Amin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu, Adish Singla.
ICML 2020.

Understanding the Power and Limitations of Teaching with Imperfect Knowledge.

Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla.
IJCAI 2020.

Get Paid to Program: Evaluating an Employment-Aware After-School Program for High School Women of Color.

Dana McFarlane, Elissa M. Redmiles.
ITiCSE 2020.

NEVAE: A Deep Generative Model for Molecular Graphs.

Bidisha Samanta, Abir De, Gourhari Jana, Vicenç Gómez, Pratim Kumar Chattaraj, Niloy Ganguly, Manuel Gomez-Rodriguez.
J. Mach. Learn. Res. 2020.

Decisions, Counterfactual Explanations and Strategic Behavior.

Stratis Tsirtsis, Manuel Gomez Rodriguez.
NeurIPS 2020.

Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction.

Mariya Toneva, Otilia Stretcu, Barnabás Póczos, Leila Wehbe, Tom M. Mitchell.
NeurIPS 2020.

Synthesizing Tasks for Block-based Programming.

Umair Z. Ahmed, Maria Christakis, Aleksandr Efremov, Nigel Fernandez, Ahana Ghosh, Abhik Roychoudhury, Adish Singla.
NeurIPS 2020.

Task-agnostic Exploration in Reinforcement Learning.

Xuezhou Zhang, Yuzhe Ma, Adish Singla.
NeurIPS 2020.

Tracking progress towards malaria elimination in China: Individual-level estimates of transmission and its spatiotemporal variation using a diffusion network approach.

Isobel Routledge, Shengjie Lai, Katherine E. Battle, Azra C. Ghani, Manuel Gomez-Rodriguez, Kyle Gustafson, Swapnil Mishra, Juliette Unwin, Joshua L. Proctor, Andrew J. Tatem, Zhongjie Li, Samir Bhatt.
PLoS Comput. Biol. 2020.

On the Desiderata for Online Altruism: Nudging for Equitable Donations.

Nuno Mota, Abhijnan Chakraborty, Asia J. Biega, Krishna P. Gummadi, Hoda Heidari.
Proc. ACM Hum. Comput. Interact. 2020.

Fair Enough: Improving Fairness in Budget-Constrained Decision Making Using Confidence Thresholds.

Michiel A. Bakker, Humberto Riverón Valdés, Duy Patrick Tu, Krishna P. Gummadi, Kush R. Varshney, Adrian Weller, Alex Pentland.
SafeAI@AAAI 2020.

On the design of consequential ranking algorithms.

Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez Rodriguez.
UAI 2020.

Fair Inputs and Fair Outputs: The Incompatibility of Fairness in Privacy and Accuracy.

Bashir Rastegarpanah, Mark Crovella, Krishna P. Gummadi.
UMAP (Adjunct Publication) 2020.

A Comprehensive Quality Evaluation of Security and Privacy Advice on the Web.

Elissa M. Redmiles, Noel Warford, Amritha Jayanti, Aravind Koneru, Sean Kross, Miraida Morales, Rock Stevens, Michelle L. Mazurek.
USENIX Security Symposium 2020.

Can A User Guess What Her Followers Want?

Abir De, Adish Singla, Utkarsh Upadhyay, Manuel Gomez-Rodriguez.
WSDM 2020.

FairRec: Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms.

Gourab K. Patro, Arpita Biswas, Niloy Ganguly, Krishna P. Gummadi, Abhijnan Chakraborty.
WWW 2020.

Bayesian Fairness.

Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic.
AAAI 2019.

Iterative Classroom Teaching.

Teresa Yeo, Parameswaran Kamalaruban, Adish Singla, Arpit Merchant, Thibault Asselborn, Louis Faucon, Pierre Dillenbourg, Volkan Cevher.
AAAI 2019.

NeVAE: A Deep Generative Model for Molecular Graphs

Bidisha Samanta, Abir De, Gourhari Jana, Pratim Kumar Chattaraj, Niloy Ganguly, Manuel Gomez Rodriguez.
AAAI 2019.

New Phone, Who Dis? Modeling Millennials' Backup Behavior.

Elissa M. Redmiles, Eszter Hargittai.
ACM Trans. Web 2019.

How Do Fairness Definitions Fare?: Examining Public Attitudes Towards Algorithmic Definitions of Fairness.

Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu.
AIES 2019.

Loss-Aversively Fair Classification.

Junaid Ali, Muhammad Bilal Zafar, Adish Singla, Krishna P. Gummadi.
AIES 2019.

Foundations for Fair Algorithmic Decision Making.

Krishna P. Gummadi.
EGC 2019.

Comparing and Developing Tools to Measure the Readability of Domain-Specific Texts.

Elissa M. Redmiles, Lisa Maszkiewicz, Emily Hwang, Dhruv Kuchhal, Everest Liu, Miraida Morales, Denis Peskov, Sudha Rao, Rock Stevens, Kristina Gligoric, Sean Kross, Michelle L. Mazurek, Hal Daumé III.
EMNLP/IJCNLP 2019.

A Moral Framework for Understanding Fair ML through Economic Models of Equality of Opportunity.

Hoda Heidari, Michele Loi, Krishna P. Gummadi, Andreas Krause.
FAT 2019.

Analyzing Biases in Perception of Truth in News Stories and Their Implications for Fact Checking.

Mahmoudreza Babaei, Abhijnan Chakraborty, Juhi Kulshrestha, Elissa M. Redmiles, Meeyoung Cha, Krishna P. Gummadi.
FAT 2019.

Equality of Voice: Towards Fair Representation in Crowdsourced Top-K Recommendations.

Abhijnan Chakraborty, Gourab K. Patro, Niloy Ganguly, Krishna P. Gummadi, Patrick Loiseau.
FAT 2019.

On Microtargeting Socially Divisive Ads: A Case Study of Russia-Linked Ad Campaigns on Facebook.

Filipe Nunes Ribeiro, Koustuv Saha, Mahmoudreza Babaei, Lucas Henrique, Johnnatan Messias, Fabrício Benevenuto, Oana Goga, Krishna P. Gummadi, Elissa M. Redmiles.
FAT 2019.

iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making.

Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum.
ICDE 2019.

An Empirical Study of Example Forgetting during Deep Neural Network Learning.

Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, Geoffrey J. Gordon.
ICLR (Poster) 2019.

Efficient learning of smooth probability functions from Bernoulli tests with guarantees.

Paul Rolland, Ali Kavis, Alexander Immer, Adish Singla, Volkan Cevher.
ICML 2019.

Learning to Collaborate in Markov Decision Processes.

Goran Radanovic, Rati Devidze, David C. Parkes, Adish Singla.
ICML 2019.

On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning.

Hoda Heidari, Vedant Nanda, Krishna P. Gummadi.
ICML 2019.

"I Just Want to Feel Safe": A Diary Study of Safety Perceptions on Social Media.

Elissa M. Redmiles, Jessica E. Bodford, Lindsay Blackwell.
ICWSM 2019.

Applied Digital Threat Modeling: It Works.

Rock Stevens, Daniel Votipka, Elissa M. Redmiles, Colin Ahern, Michelle L. Mazurek.
IEEE Secur. Priv. 2019.

"Should I Worry?" A Cross-Cultural Examination of Account Security Incident Response.

Elissa M. Redmiles.
IEEE Symposium on Security and Privacy 2019.

How Well Do My Results Generalize? Comparing Security and Privacy Survey Results from MTurk, Web, and Telephone Samples.

Elissa M. Redmiles, Sean Kross, Michelle L. Mazurek.
IEEE Symposium on Security and Privacy 2019.

Editorial Versus Audience Gatekeeping: Analyzing News Selection and Consumption Dynamics in Online News Media.

Abhijnan Chakraborty, Saptarshi Ghosh, Niloy Ganguly, Krishna P. Gummadi.
IEEE Trans. Comput. Soc. Syst. 2019.

Interactive Teaching Algorithms for Inverse Reinforcement Learning.

Parameswaran Kamalaruban, Rati Devidze, Volkan Cevher, Adish Singla.
IJCAI 2019.

The Price of Local Fairness in Multistage Selection.

Vitalii Emelianov, George Arvanitakis, Nicolas Gast, Krishna P. Gummadi, Patrick Loiseau.
IJCAI 2019.

Optimizing the recency-relevance-diversity trade-offs in non-personalized news recommendations.

Abhijnan Chakraborty, Saptarshi Ghosh, Niloy Ganguly, Krishna P. Gummadi.
Inf. Retr. J. 2019.

Search bias quantification: investigating political bias in social media and web search.

Juhi Kulshrestha, Motahhare Eslami, Johnnatan Messias, Muhammad Bilal Zafar, Saptarshi Ghosh, Krishna P. Gummadi, Karrie Karahalios.
Inf. Retr. J. 2019.

Fairness Constraints: A Flexible Approach for Fair Classification.

Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna P. Gummadi.
J. Mach. Learn. Res. 2019.

Two-Sided Fairness for Repeated Matchings in Two-Sided Markets: A Case Study of a Ride-Hailing Platform.

Tom Sühr, Asia J. Biega, Meike Zehlike, Krishna P. Gummadi, Abhijnan Chakraborty.
KDD 2019.

Inducing brain-relevant bias in natural language processing models.

Dan Schwartz, Mariya Toneva, Leila Wehbe.
NeurIPS 2019.

Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain).

Mariya Toneva, Leila Wehbe.
NeurIPS 2019.

Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints.

Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla.
NeurIPS 2019.

Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models.

Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin (Jerry) Zhu, Adish Singla.
NeurIPS 2019.

Teaching Multiple Concepts to a Forgetful Learner.

Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla.
NeurIPS 2019.

Human Decision Making with Machine Assistance: An Experiment on Bailing and Jailing.

Nina Grgic-Hlaca, Christoph Engel, Krishna P. Gummadi.
Proc. ACM Hum. Comput. Interact. 2019.

Lethe: Conceal Content Deletion from Persistent Observers.

Mohsen Minaei, Mainack Mondal, Patrick Loiseau, Krishna P. Gummadi, Aniket Kate.
Proc. Priv. Enhancing Technol. 2019.

Operationalizing Individual Fairness with Pairwise Fair Representations.

Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum.
Proc. VLDB Endow. 2019.

Enhancing Human Learning via Spaced Repetition Optimization

Behzad Tabibian, Utkarsh Upadhyay, Abir De, Ali Zarezade, Bernhard Schoelkopf, Manuel Gomez Rodriguez.
Proceedings of the National Academy of Sciences (PNAS) 2019.

The Responsibility Challenge for Data.

H. V. Jagadish, Francesco Bonchi, Tina Eliassi-Rad, Lise Getoor, Krishna P. Gummadi, Julia Stoyanovich.
SIGMOD Conference 2019.

Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems.

Bashir Rastegarpanah, Krishna P. Gummadi, Mark Crovella.
WSDM 2019.

On the Complexity of Opinions and Online Discussions.

Utkarsh Upadhyay, Abir De, Aasish Pappu, Manuel Gomez-Rodriguez.
WSDM 2019.

Auditing Offline Data Brokers via Facebook's Advertising Platform.

Giridhari Venkatadri, Piotr Sapiezynski, Elissa M. Redmiles, Alan Mislove, Oana Goga, Michelle L. Mazurek, Krishna P. Gummadi.
WWW 2019.

Economic Theories of Distributive Justice for Fair Machine Learning.

Krishna P. Gummadi, Hoda Heidari.
WWW 2019.

On the Impact of Choice Architectures on Inequality in Online Donation Platforms.

Abhijnan Chakraborty, Nuno Mota, Asia J. Biega, Krishna P. Gummadi, Hoda Heidari.
WWW 2019.

Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning.

Nina Grgic-Hlaca, Muhammad Bilal Zafar, Krishna P. Gummadi, Adrian Weller.
AAAI 2018.

Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints.

Goran Radanovic, Adish Singla, Andreas Krause, Boi Faltings.
AAAI 2018.

Learning to Interact With Learning Agents.

Adish Singla, Seyed Hamed Hassani, Andreas Krause.
AAAI 2018.

Learning User Preferences to Incentivize Exploration in the Sharing Economy.

Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause.
AAAI 2018.

Partial Truthfulness in Minimal Peer Prediction Mechanisms With Limited Knowledge.

Goran Radanovic, Boi Faltings.
AAAI 2018.

Purple Feed: Identifying High Consensus News Posts on Social Media.

Mahmoudreza Babaei, Juhi Kulshrestha, Abhijnan Chakraborty, Fabrício Benevenuto, Krishna P. Gummadi, Adrian Weller.
AIES 2018.

An Overview of Machine Teaching

Xiaojin Zhu, Adish Singla, Sandra Zilles, Anna N. Rafferty.
arXiv

"What was that site doing with my Facebook password?": Designing Password-Reuse Notifications.

Maximilian Golla, Miranda Wei, Juliette Hainline, Lydia Filipe, Markus Dürmuth, Elissa M. Redmiles, Blase Ur.
CCS 2018.

Asking for a Friend: Evaluating Response Biases in Security User Studies.

Elissa M. Redmiles, Ziyun Zhu, Sean Kross, Dhruv Kuchhal, Tudor Dumitras, Michelle L. Mazurek.
CCS 2018.

Equitable Security: Optimizing Distribution of Nudges and Resources.

Elissa M. Redmiles, John P. Dickerson, Krishna P. Gummadi, Michelle L. Mazurek.
CCS 2018.

Examining the Demand for Spam: Who Clicks?

Elissa M. Redmiles, Neha Chachra, Brian Waismeyer.
CHI 2018.

Dancing Pigs or Externalities?: Measuring the Rationality of Security Decisions.

Elissa M. Redmiles, Michelle L. Mazurek, John P. Dickerson.
EC 2018.

Data-Driven Approach Towards a Personalized Curriculum.

Michael Backenköhler, Felix Scherzinger, Adish Singla, Verena Wolf.
EDM 2018.

Potential for Discrimination in Online Targeted Advertising.

Till Speicher, Muhammad Ali, Giridhari Venkatadri, Filipe Nunes Ribeiro, George Arvanitakis, Fabrício Benevenuto, Krishna P. Gummadi, Patrick Loiseau, Alan Mislove.
FAT 2018.

Exploring User Mental Models of End-to-End Encrypted Communication Tools.

Ruba Abu-Salma, Elissa M. Redmiles, Blase Ur, Miranda Wei.
FOCI @ USENIX Security Symposium 2018.

Treads: Transparency-Enhancing Ads.

Giridhari Venkatadri, Alan Mislove, Krishna P. Gummadi.
HotNets 2018.

Blind Justice: Fairness with Encrypted Sensitive Attributes.

Niki Kilbertus, Adrià Gascón, Matt J. Kusner, Michael Veale, Krishna P. Gummadi, Adrian Weller.
ICML 2018.

Diversifying the Next Generation of Information Scientists: Six Years of Implementation and Outcomes for a Year-Long REU Program.

Kayla M. Booth, Bryan Dosono, Elissa M. Redmiles, Miraida Morales, Michael Depew, Rosta Farzan, Everett Herman, Keith Trahan, Cindy Tananis.
iConference 2018.

Media Bias Monitor: Quantifying Biases of Social Media News Outlets at Large-Scale.

Filipe Nunes Ribeiro, Lucas Henrique, Fabrício Benevenuto, Abhijnan Chakraborty, Juhi Kulshrestha, Mahmoudreza Babaei, Krishna P. Gummadi.
ICWSM 2018.

Net Benefits: Digital Inequities in Social Capital, Privacy Preservation, and Digital Parenting Practices of U.S. Social Media Users.

Elissa M. Redmiles.
ICWSM 2018.

Hackers vs. Testers: A Comparison of Software Vulnerability Discovery Processes.

Daniel Votipka, Rock Stevens, Elissa M. Redmiles, Jeremy Hu, Michelle L. Mazurek.
IEEE Symposium on Security and Privacy 2018.

Privacy Risks with Facebook's PII-Based Targeting: Auditing a Data Broker's Advertising Interface.

Giridhari Venkatadri, Athanasios Andreou, Yabing Liu, Alan Mislove, Krishna P. Gummadi, Patrick Loiseau, Oana Goga.
IEEE Symposium on Security and Privacy 2018.

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices.

Till Speicher, Hoda Heidari, Nina Grgic-Hlaca, Krishna P. Gummadi, Adish Singla, Adrian Weller, Muhammad Bilal Zafar.
KDD 2018.

Investigating Ad Transparency Mechanisms in Social Media: A Case Study of Facebooks Explanations.

Athanasios Andreou, Giridhari Venkatadri, Oana Goga, Krishna P. Gummadi, Patrick Loiseau, Alan Mislove.
NDSS 2018.

Deep Reinforcement Learning of Marked Temporal Point Processes.

Utkarsh Upadhyay, Abir De, Manuel Gomez Rodriguez.
NeurIPS 2018.

Enhancing the Accuracy and Fairness of Human Decision Making.

Isabel Valera, Adish Singla, Manuel Gomez Rodriguez.
NeurIPS 2018.

Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making.

Hoda Heidari, Claudio Ferrari, Krishna P. Gummadi, Andreas Krause.
NeurIPS 2018.

Teaching Inverse Reinforcement Learners via Features and Demonstrations.

Luis Haug, Sebastian Tschiatschek, Adish Singla.
NeurIPS 2018.

Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners.

Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue.
NeurIPS 2018.

Equity of Attention: Amortizing Individual Fairness in Rankings.

Asia J. Biega, Krishna P. Gummadi, Gerhard Weikum.
SIGIR 2018.

Ethics Emerging: the Story of Privacy and Security Perceptions in Virtual Reality.

Devon Adams, Alseny Bah, Catherine Barwulor, Nureli Musaby, Kadeem Pitkin, Elissa M. Redmiles.
SOUPS @ USENIX Security Symposium 2018.

The Battle for New York: A Case Study of Applied Digital Threat Modeling at the Enterprise Level.

Rock Stevens, Daniel Votipka, Elissa M. Redmiles, Colin Ahern, Patrick Sweeney, Michelle L. Mazurek.
USENIX Security Symposium 2018.

Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation.

Jooyeon Kim, Behzad Tabibian, Alice Oh, Bernhard Schölkopf, Manuel Gomez-Rodriguez.
WSDM 2018.

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution.

Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Yichen Wang, Shuang Li, Hongyuan Zha, Le Song.
WWW 2018.

Fake News Detection in Social Networks via Crowd Signals.

Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause.
WWW 2018.

Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction.

Nina Grgic-Hlaca, Elissa M. Redmiles, Krishna P. Gummadi, Adrian Weller.
WWW 2018.

On the Causal Effect of Badges.

Tomasz Kusmierczyk, Manuel Gomez-Rodriguez.
WWW 2018.

Selecting Sequences of Items via Submodular Maximization.

Sebastian Tschiatschek, Adish Singla, Andreas Krause.
AAAI 2017.

Fairness Constraints: Mechanisms for Fair Classification

Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, Krishna P. Gummadi.
AISTATS 2017.

Where is the Digital Divide?: A Survey of Security, Privacy, and Socioeconomics.

Elissa M. Redmiles, Sean Kross, Michelle L. Mazurek.
CHI 2017.

Learning to Un-Rank: Quantifying Search Exposure for Users in Online Communities.

Asia J. Biega, Azin Ghazimatin, Hakan Ferhatosmanoglu, Krishna P. Gummadi, Gerhard Weikum.
CIKM 2017.

Inside the Walled Garden: Deconstructing Facebook's Free Basics Program.

Rijurekha Sen, Sohaib Ahmad, Amreesh Phokeer, Zaid Ahmed Farooq, Ihsan Ayyub Qazi, David R. Choffnes, Krishna P. Gummadi.
Comput. Commun. Rev. 2017.

Quantifying Search Bias: Investigating Sources of Bias for Political Searches in Social Media

Juhi Kulshrestha, Motahhare Eslami, Johnnatan Messias, Muhammad Bilal Zafar, Saptarshi Ghosh, Krishna P. Gummadi, Karrie G. Karahalios.
CSCW 2017.

Lessons Learned from Using an Online Platform to Conduct Large-Scale, Online Controlled Security Experiments with Software Developers.

Christian Stransky, Yasemin Acar, Duc Cuong Nguyen, Dominik Wermke, Doowon Kim, Elissa M. Redmiles, Michael Backes, Simson L. Garfinkel, Michelle L. Mazurek, Sascha Fahl.
CSET @ USENIX Security Symposium 2017.

Reconciling Privacy and Utility in Continuous-Time Diffusion Networks.

Michael Backes, Manuel Gomez-Rodriguez, Praveen Manoharan, Bartlomiej Surma.
CSF 2017.

Game Theory for Data Science: Eliciting Truthful Information

Boi Faltings, Goran Radanovic.
Game Theory for Data Science: Eliciting Truthful Information 2017.

Leveraging Facebook's Free Basics Engine for Web Service Deployment in Developing Regions.

Siddharth Singh, Vedant Nanda, Rijurekha Sen, Satadal Sengupta, Ponnurangam Kumaraguru, Krishna P. Gummadi.
ICTD 2017.

Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations.

Abhijnan Chakraborty, Johnnatan Messias, Fabrício Benevenuto, Saptarshi Ghosh, Niloy Ganguly, Krishna P. Gummadi.
ICWSM 2017.

Longitudinal Privacy Management in Social Media: The Need for Better Controls.

Mainack Mondal, Johnnatan Messias, Saptarshi Ghosh, Krishna P. Gummadi, Aniket Kate.
IEEE Internet Comput. 2017.

Mechanismen zur Beschaffung korrekter Daten.

Boi Faltings, Goran Radanovic.
Inform. Spektrum 2017.

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Evolution.

Mehrdad Farajtabar, Yichen Wang, Manuel Gomez-Rodriguez, Shuang Li, Hongyuan Zha, Le Song.
J. Mach. Learn. Res. 2017.

Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks.

Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song.
J. Mach. Learn. Res. 2017.

Steering Social Activity: A Stochastic Optimal Control Point Of View.

Ali Zarezade, Abir De, Utkarsh Upadhyay, Hamid R. Rabiee, Manuel Gomez-Rodriguez.
J. Mach. Learn. Res. 2017.

A broad view of the ecosystem of socially engineered exploit documents

Stevens Le Blond, Cedric Gilbert, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, David Choffnes.
NDSS 2017.

From Parity to Preference-based Notions of Fairness in Classification.

Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna P. Gummadi, Adrian Weller.
NIPS 2017.

Multi-View Decision Processes: The Helper-AI Problem.

Christos Dimitrakakis, David C. Parkes, Goran Radanovic, Paul Tylkin.
NIPS 2017.

Uncovering the Spatiotemporal Patterns of Collective Social Activity

Martin Jankowiak, Manuel Gomez-Rodriguez.
SDM 2017.

An Empirical Analysis of Facebook's Free Basics.

Siddharth Singh, Vedant Nanda, Rijurekha Sen, Sohaib Ahmad, Satadal Sengupta, Amreesh Phokeer, Zaid Ahmed Farooq, Taslim Arefin Khan, Ponnurangam Kumaraguru, Ihsan Ayyub Qazi, David R. Choffnes, Krishna P. Gummadi.
SIGMETRICS (Abstracts) 2017.

You Want Me To Do What? A Design Study of Two-Factor Authentication Messages.

Elissa M. Redmiles, Everest Liu, Michelle L. Mazurek.
SOUPS 2017.

Exploring User Perceptions of Discrimination in Online Targeted Advertising.

Angelisa C. Plane, Elissa M. Redmiles, Michelle L. Mazurek, Michael Carl Tschantz.
USENIX Security Symposium 2017.

RedQueen: An Online Algorithm for Smart Broadcasting in Social Networks.

Ali Zarezade, Utkarsh Upadhyay, Hamid R. Rabiee, Manuel Gomez-Rodriguez.
WSDM 2017.

Uncovering the Dynamics of Crowdlearning and the Value of Knowledge.

Utkarsh Upadhyay, Isabel Valera, Manuel Gomez-Rodriguez.
WSDM 2017.

Distilling Information Reliability and Source Trustworthiness from Digital Traces.

Behzad Tabibian, Isabel Valera, Mehrdad Farajtabar, Le Song, Bernhard Schölkopf, Manuel Gomez-Rodriguez.
WWW 2017.

Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment.

Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna P. Gummadi.
WWW 2017.

Fairness Beyond Disparate Treatment and Disparate Impact: Learning Classification without Disparate Mistreatment

Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna Gummadi.
WWW 2017.

Modeling the Dynamics of Learning Activity on the Web.

Charalampos Mavroforakis, Isabel Valera, Manuel Gomez-Rodriguez.
WWW 2017.

Modeling the Dynamics of Online Learning Activity

Charalampos Mavroforakis, Isabel Valera, Manuel Gomez-Rodriguez.
WWW 2017.

Optimizing the Recency-Relevancy Trade-off in Online News Recommendations

Abhijnan Chakraborty, Saptarshi Ghosh, Niloy Ganguly, Krishna P. Gummadi.
WWW 2017.

Doctoral Thesis: Towards Trustworthy Social Computing Systems

Bimal Viswanath.
Technical Report MPI-SWS-2016-004 2016.

Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization.

Adish Singla, Sebastian Tschiatschek, Andreas Krause.
AAAI 2016.

Limiting the Influence of Low Quality Information in Community Sensing.

Goran Radanovic, Boi Faltings.
AAMAS 2016.

Influence Estimation and Maximization in Continuous-Time Diffusion Networks.

Manuel Gomez-Rodriguez, Le Song, Nan Du, Hongyuan Zha, Bernhard Schölkopf.
ACM Trans. Inf. Syst. 2016.

Incentives for Effort in Crowdsourcing Using the Peer Truth Serum.

Goran Radanovic, Boi Faltings, Radu Jurca.
ACM Trans. Intell. Syst. Technol. 2016.

Detecting fraud, corruption, and collusion in international development contracts: The design of a proof-of-concept automated system.

Emily Grace, Ankit Rai, Elissa M. Redmiles, Rayid Ghani.
BigData 2016.

How I Learned to be Secure: a Census-Representative Survey of Security Advice Sources and Behavior.

Elissa M. Redmiles, Sean Kross, Michelle L. Mazurek.
CCS 2016.

On the Wisdom of Experts vs. Crowds: Discovering Trustworthy Topical News in Microblogs.

Muhammad Bilal Zafar, Parantapa Bhattacharya, Niloy Ganguly, Saptarshi Ghosh, Krishna P. Gummadi.
CSCW 2016.

Evaluating Task-Dependent Taxonomies for Navigation.

Yuyin Sun, Adish Singla, Tori Qiao Yan, Andreas Krause, Dieter Fox.
HCOMP 2016.

Learning and Feature Selection under Budget Constraints in Crowdsourcing.

Besmira Nushi, Adish Singla, Andreas Krause, Donald Kossmann.
HCOMP 2016.

Learning to Scale Payments in Crowdsourcing with PropeRBoost.

Goran Radanovic, Boi Faltings.
HCOMP 2016.

Actively Learning Hemimetrics with Applications to Eliciting User Preferences.

Adish Singla, Sebastian Tschiatschek, Andreas Krause.
ICML 2016.

Dissemination Biases of Social Media Channels: On the Topical Coverage of Socially Shared News.

Abhijnan Chakraborty, Saptarshi Ghosh, Niloy Ganguly, Krishna P. Gummadi.
ICWSM 2016.

Distinguishing between Topical and Non-Topical Information Diffusion Mechanisms in Social Media.

Przemyslaw A. Grabowicz, Niloy Ganguly, Krishna P. Gummadi.
ICWSM 2016.

Message Impartiality in Social Media Discussions.

Muhammad Bilal Zafar, Krishna P. Gummadi, Cristian Danescu-Niculescu-Mizil.
ICWSM 2016.

Scalable Urban Data Collection from the Web.

Rijurekha Sen, Daniele Quercia, Carmen Karina Vaca Ruiz, Krishna P. Gummadi.
ICWSM 2016.

Detecting fraud, corruption, and collusion in international development contracts: The design of a proof-of-concept automated system.

Emily Grace, Ankit Rai, Elissa M. Redmiles, Rayid Ghani.
IEEE BigData 2016.

I Think They're Trying to Tell Me Something: Advice Sources and Selection for Digital Security.

Elissa M. Redmiles, Amelia R. Malone, Michelle L. Mazurek.
IEEE Symposium on Security and Privacy 2016.

On the Free Bridge Across the Digital Divide: Assessing the Quality of Facebook's Free Basics Service.

Rijurekha Sen, Hasnain Ali Pirzada, Amreesh Phokeer, Zaid Ahmed Farooq, Satadal Sengupta, David R. Choffnes, Krishna P. Gummadi.
IMC 2016.

Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm.

Manuel Gomez-Rodriguez, Le Song, Hadi Daneshmand, Bernhard Schölkopf.
J. Mach. Learn. Res. 2016.

Recurrent Marked Temporal Point Processes: Embedding Event History to Vector.

Nan Du, Hanjun Dai, Rakshit Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, Le Song.
KDD 2016.

Smart Broadcasting: Do You Want to be Seen?

Mohammad Reza Karimi, Erfan Tavakoli, Mehrdad Farajtabar, Le Song, Manuel Gomez-Rodriguez.
KDD 2016.

Learning and Incentives in Crowd-Powered Systems.

Adish Singla.
Learning and Incentives in Crowd-Powered Systems. 2016.

Learning and Forecasting Opinion Dynamics in Social Networks.

Abir De, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, Manuel Gomez-Rodriguez.
NIPS 2016.

R-Susceptibility: An IR-Centric Approach to Assessing Privacy Risks for Users in Online Communities

Joanna Asia Biega, Krishna P. Gummadi, Ida Mele, Dragan Milchevski, Christos Tryfonopoulos, Gerhard Weikum.
SIGIR 2016.

Forgetting in Social Media: Understanding and Controlling Longitudinal Exposure of Socially Shared Data

Mainack Mondal, Johnnatan Messias, Saptarshi Ghosh, Krishna P. Gummadi, Aniket Kate.
SOUPS 2016.

On Profile Linkability despite Anonymity in Social Media Systems.

Michael Backes, Pascal Berrang, Oana Goga, Krishna P. Gummadi, Praveen Manoharan.
WPES@CCS 2016.

On the Efficiency of the Information Networks in Social Media.

Mahmoudreza Babaei, Przemyslaw A. Grabowicz, Isabel Valera, Krishna P. Gummadi, Manuel Gomez-Rodriguez.
WSDM 2016.

Strengthening Weak Identities Through Inter-Domain Trust Transfer

Giridhari Venkatadri, Oana Goga, Changtao Zhong, Bimal Viswanath, Krishna P. Gummadi, Nishanth R. Sastry.
WWW 2016.

Incentives for Subjective Evaluations with Private Beliefs.

Goran Radanovic, Boi Faltings.
AAAI 2015.

Incentivizing Users for Balancing Bike Sharing Systems.

Adish Singla, Marco Santoni, Gábor Bartók, Pratik Mukerji, Moritz Meenen, Andreas Krause.
AAAI 2015.

Incentive Schemes for Participatory Sensing.

Goran Radanovic, Boi Faltings.
AAMAS 2015.

Sampling Content from Online Social Networks: Comparing Random vs. Expert Sampling of the Twitter Stream.

Muhammad Bilal Zafar, Parantapa Bhattacharya, Niloy Ganguly, Krishna P. Gummadi, Saptarshi Ghosh.
ACM Trans. Web 2015.

Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades.

Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Mohammad Zamani, Nan Du, Hongyuan Zha, Le Song.
AISTATS 2015.

Strength in Numbers: Robust Tamper Detection in Crowd Computations

Bimal Viswanath, Muhammad Ahmad Bashir, Muhammad Bilal Zafar, Simon Bouget, Saikat Guha, Krishna P. Gummadi, Aniket Kate, Alan Mislove.
COSN 2015.

Fairness Constraints: A Mechanism for Fair Classification.

Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna Gummadi.
FATML 2015.

Applying artificial vision models to human scene understanding.

Elissa Michele Aminoff, Mariya Toneva, Abhinav Shrivastava, Xinlei Chen, Ishan Misra, Abhinav Gupta, Michael J. Tarr.
Frontiers Comput. Neurosci. 2015.

Crowd Access Path Optimization: Diversity Matters.

Besmira Nushi, Adish Singla, Anja Gruenheid, Erfan Zamanian, Andreas Krause, Donald Kossmann.
HCOMP 2015.

Learning to Hire Teams.

Adish Singla, Eric Horvitz, Pushmeet Kohli, Andreas Krause.
HCOMP 2015.

Modeling Adoption and Usage of Competing Products.

Isabel Valera, Manuel Gomez-Rodriguez.
ICDM 2015.

Characterizing Information Diets of Social Media Users.

Juhi Kulshrestha, Muhammad Bilal Zafar, Lisette Espin Noboa, Krishna P. Gummadi, Saptarshi Ghosh.
ICWSM 2015.

On the Users' Efficiency in the Twitter Information Network.

Mahmoudreza Babaei, Przemyslaw A. Grabowicz, Isabel Valera, Manuel Gomez-Rodriguez.
ICWSM 2015.

The Many Shades of Anonymity: Characterizing Anonymous Social Media Content

Denzil Correa, Leandro Araujo Silva, Mainack Mondal, Fabricio Benevenuto, Krishna P. Gummadi.
ICWSM 2015.

Building Hierarchies of Concepts via Crowdsourcing.

Yuyin Sun, Adish Singla, Dieter Fox, Andreas Krause.
IJCAI 2015.

Information Gathering in Networks via Active Exploration.

Adish Singla, Eric Horvitz, Pushmeet Kohli, Ryen White, Andreas Krause.
IJCAI 2015.

The Doppelgänger Bot Attack: Exploring Identity Impersonation in Online Social Networks

Oana Goga, Giridhari Venkatadri, Krishna P. Gummadi.
IMC 2015.

On the Reliability of Profile Matching Across Large Online Social Networks

Oana Goga, Patrick Loiseau, Robin Sommer, Renata Teixeira, Krishna P. Gummadi.
KDD 2015.

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution.

Mehrdad Farajtabar, Yichen Wang, Manuel Gomez-Rodriguez, Shuang Li, Hongyuan Zha, Le Song.
NIPS 2015.

A Classroom Tested Accessible Multimedia Resource for Engaging Underrepresented Students in Computing: The University of Maryland Curriculum In A Box.

Elissa M. Redmiles, Mary Allison Abad, Isabella Coronado, Sean Kross, Amelia Malone.
SIGCSE 2015.

Incentivizing truthful responses with the logarithmic peer truth serum.

Goran Radanovic, Boi Faltings.
UbiComp/ISWC Adjunct 2015.

Co-evolutionary Dynamics of Information Diffusion and Network Structure.

Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Yichen Wang, Shuang Li, Hongyuan Zha, Le Song.
WWW 2015.

Microscopic Description and Prediction of Information Diffusion in Social Media: Quantifying the Impact of Topical Interests.

Przemyslaw A. Grabowicz, Niloy Ganguly, Krishna P. Gummadi.
WWW 2015.

Incentives for Truthful Information Elicitation of Continuous Signals.

Goran Radanovic, Boi Faltings.
AAAI 2014.

Stochastic Privacy.

Adish Singla, Eric Horvitz, Ece Kamar, Ryen White.
AAAI 2014.

Quantifying Web-Search Privacy.

Arthur Gervais, Reza Shokri, Adish Singla, Srdjan Capkun, Vincent Lenders.
CCS 2014.

Does content determine information popularity in social media?: a case study of youtube videos' content and their popularity.

Flavio Figueiredo, Jussara M. Almeida, Fabrício Benevenuto, Krishna P. Gummadi.
CHI 2014.

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