Jon Schneider
28 papers · 2018–2026 · 5 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (7) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (5) 🐝 Cross-Pollinator (6)
🐣
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 (3)
IJCAI (1)
Top co-authors
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
Efficient Opportunistic Approachability
ALT 2026
Best of Both Worlds: Regret Minimization versus Minimax Play
ICML 2025
Computing Optimal Regularizers for Online Linear Optimization
COLT 2025
Rate-Preserving Reductions for Blackwell Approachability
COLT 2025
Full Swap Regret and Discretized Calibration
ALT 2025
Adversarial Online Learning with Temporal Feedback Graphs
COLT 2024
Contracting with a Learning Agent
NIPS 2024
Convergence of No-Swap-Regret Dynamics in Self-Play
NIPS 2024
Online Learning with Bounded Recall
ICML 2024
Optimal No-Regret Learning for One-Sided Lipschitz Functions
ICML 2023
Optimal cross-learning for contextual bandits with unknown context distributions
NIPS 2023
Is Learning in Games Good for the Learners?
NIPS 2023
Pseudonorm Approachability and Applications to Regret Minimization
ALT 2023
U-Calibration: Forecasting for an Unknown Agent
COLT 2023
Strategizing against Learners in Bayesian Games
COLT 2022
Anonymous Bandits for Multi-User Systems
NIPS 2022
Corruption-Robust Contextual Search through Density Updates
COLT 2022
Reserve Price Optimization for First Price Auctions in Display Advertising
ICML 2021
Margin-Independent Online Multiclass Learning via Convex Geometry
NIPS 2021
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms
NIPS 2021
Jointly Learning Prices and Product Features
IJCAI 2021
Costly Zero Order Oracles
COLT 2020
Myersonian Regression
NIPS 2020
Multi-armed Bandit Problems with Strategic Arms
COLT 2019
Contextual Bandits with Cross-Learning
NIPS 2019
Strategizing against No-regret Learners
NIPS 2019
Prior-Free Dynamic Auctions with Low Regret Buyers
NIPS 2019
Contextual Pricing for Lipschitz Buyers
NIPS 2018