Jon Schneider

27 papers · 2018–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (6) 🗺️ Taxonomy Completionist (26) 🏃 Academic Marathon (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) 🏆 Keyword Champion (3) 🔬 Deep Specialist (15) 🔥 Unstoppable (8) ⚡ Prolific Year (5) 💎 Century Club (27) ❓ The Questioner 🗃️ Keyword Collector (88)

Conferences

NIPS (12) COLT (8) ICML (4) ALT (2) IJCAI (1)

Top co-authors

Renato Paes Leme (6) Balasubramanian Sivan (5) Guru Guruganesh (4) Yishay Mansour (3) Mehryar Mohri (3) Renato Leme (3) Allen Liu (2) Vahab Mirrokni (2) S. Matthew Weinberg (2) Yuan Deng (2)

Keywords

regret bound (11) online learning (9) regret minimization (4) contextual bandit (3) repeated game (3) no-regret learning (3) game theory (3) principal-agent problem (2) nash equilibrium (2) adversarial learning (2) stackelberg equilibrium (2) revenue optimization (2) online algorithm (2) convex optimization (2) multi-armed bandit (2) no-regret algorithm (2) multi-agent learning (1) nearest neighbor (1) gradient-based optimization (1) online advertising (1)

Papers

Rate-Preserving Reductions for Blackwell Approachability COLT 2025

Computing Optimal Regularizers for Online Linear Optimization COLT 2025

Best of Both Worlds: Regret Minimization versus Minimax Play ICML 2025

Full Swap Regret and Discretized Calibration ALT 2025

Online Learning with Bounded Recall ICML 2024

Adversarial Online Learning with Temporal Feedback Graphs COLT 2024

Convergence of No-Swap-Regret Dynamics in Self-Play NIPS 2024

Contracting with a Learning Agent NIPS 2024

Optimal cross-learning for contextual bandits with unknown context distributions NIPS 2023

U-Calibration: Forecasting for an Unknown Agent COLT 2023

Optimal No-Regret Learning for One-Sided Lipschitz Functions ICML 2023

Is Learning in Games Good for the Learners? NIPS 2023

Pseudonorm Approachability and Applications to Regret Minimization ALT 2023

Corruption-Robust Contextual Search through Density Updates COLT 2022

Anonymous Bandits for Multi-User Systems NIPS 2022

Strategizing against Learners in Bayesian Games COLT 2022

Jointly Learning Prices and Product Features IJCAI 2021

Contextual Recommendations and Low-Regret Cutting-Plane Algorithms NIPS 2021

Margin-Independent Online Multiclass Learning via Convex Geometry NIPS 2021

Reserve Price Optimization for First Price Auctions in Display Advertising ICML 2021

Costly Zero Order Oracles COLT 2020

Myersonian Regression NIPS 2020

Strategizing against No-regret Learners NIPS 2019

Contextual Bandits with Cross-Learning NIPS 2019

Prior-Free Dynamic Auctions with Low Regret Buyers NIPS 2019

Multi-armed Bandit Problems with Strategic Arms COLT 2019

Contextual Pricing for Lipschitz Buyers NIPS 2018