Varying the Number of Signals in Matching Markets. - Meena Jagadeesan; Alexander Wei 001 (WINE, 2018)

Simple Analysis of Sparse, Sign-Consistent JL. - Meena Jagadeesan (APPROX-RANDOM, 2019)

Understanding Sparse JL for Feature Hashing. - Meena Jagadeesan (NeurIPS, 2019)

Individual Fairness in Sponsored Search Auctions. - Shuchi Chawla 001; Christina Ilvento; Meena Jagadeesan (CoRR, 2019)

Multi-category fairness in sponsored search auctions. - Christina Ilvento; Meena Jagadeesan; Shuchi Chawla 001 (FAT*, 2020)

Individual Fairness in Pipelines. - Cynthia Dwork; Christina Ilvento; Meena Jagadeesan (FORC, 2020)

From Worst-Case to Average-Case Analysis: Accurate Latency Predictions for Key-Value Storage Engines. - Meena Jagadeesan; Garrett Tanzer (SIGMOD Conference, 2020)

Fairness in ad auctions through inverse proportionality. - Shuchi Chawla 001; Meena Jagadeesan (CoRR, 2020)

Alternative Microfoundations for Strategic Classification. - Meena Jagadeesan; Celestine Mendler-Dünner; Moritz Hardt (ICML, 2021)

Learning Equilibria in Matching Markets from Bandit Feedback. - Meena Jagadeesan; Alexander Wei 001; Yixin Wang 002; Michael I. Jordan; Jacob Steinhardt (NeurIPS, 2021)

Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine. - Subarna Chatterjee; Meena Jagadeesan; Wilson Qin; Stratos Idreos (Proc. VLDB Endow., 2021)

Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm. - Meena Jagadeesan; Ilya P. Razenshteyn; Suriya Gunasekar (COLT, 2022)

Regret Minimization with Performative Feedback. - Meena Jagadeesan; Tijana Zrnic; Celestine Mendler-Dünner (ICML, 2022)

Individual Fairness in Advertising Auctions Through Inverse Proportionality. - Shuchi Chawla 001; Meena Jagadeesan (ITCS, 2022)

Performative Power. - Moritz Hardt; Meena Jagadeesan; Celestine Mendler-Dünner (NeurIPS, 2022)

Competition, Alignment, and Equilibria in Digital Marketplaces. - Meena Jagadeesan; Michael I. Jordan; Nika Haghtalab (AAAI, 2023)

Supply-Side Equilibria in Recommender Systems. - Meena Jagadeesan; Nikhil Garg 001; Jacob Steinhardt (NeurIPS, 2023)

Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition. - Meena Jagadeesan; Michael I. Jordan; Jacob Steinhardt; Nika Haghtalab (NeurIPS, 2023)

Incentivizing High-Quality Content in Online Recommender Systems. - Xinyan Hu; Meena Jagadeesan; Michael I. Jordan; Jacob Steinhardt (CoRR, 2023)

Learning Equilibria in Matching Markets with Bandit Feedback. - Meena Jagadeesan; Alexander Wei 001; Yixin Wang 002; Michael I. Jordan; Jacob Steinhardt (J. ACM, 2023)

Can Probabilistic Feedback Drive User Impacts in Online Platforms? - Jessica Dai; Bailey Flanigan; Meena Jagadeesan; Nika Haghtalab; Chara Podimata (AISTATS, 2024)

Impact of Decentralized Learning on Player Utilities in Stackelberg Games. - Kate Donahue; Nicole Immorlica; Meena Jagadeesan; Brendan Lucier; Aleksandrs Slivkins (ICML, 2024)

Feedback Loops With Language Models Drive In-Context Reward Hacking. - Alexander Pan; Erik Jones; Meena Jagadeesan; Jacob Steinhardt (ICML, 2024)

Clickbait vs. Quality: How Engagement-Based Optimization Shapes the Content Landscape in Online Platforms. - Nicole Immorlica; Meena Jagadeesan; Brendan Lucier (WWW, 2024)

Safety vs. Performance: How Multi-Objective Learning Reduces Barriers to Market Entry. - Meena Jagadeesan; Michael I. Jordan; Jacob Steinhardt (CoRR, 2024)

Accounting for AI and Users Shaping One Another: The Role of Mathematical Models. - Sarah Dean; Evan Dong; Meena Jagadeesan; Liu Leqi (Trans. Mach. Learn. Res., 2025)

Flattening Supply Chains: When do Technology Improvements lead to Disintermediation? - S. Nageeb Ali; Nicole Immorlica; Meena Jagadeesan; Brendan Lucier (CoRR, 2025)