David Simchi-Levi
22 papers · 2018–2025 · 4 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
🌍 Conference Polyglot (4) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (7)
🌍
Conference Polyglot
(4)
🏃
Academic Marathon
(7)
🏆
Keyword Champion
(2)
🗃️
Keyword Collector
(94)
💎
Century Club
(22)
🔥
Unstoppable
(8)
⚡
Prolific Year
(5)
Conferences
NIPS (9)
ICML (7)
AISTATS (4)
COLT (2)
Top co-authors
Keywords
multi-armed bandit
(6)
regret bound
(6)
online learning
(5)
sample complexity
(4)
dynamic regret
(3)
dynamic pricing
(3)
experimental design
(3)
upper confidence bound
(3)
expected regret
(2)
regret minimization
(2)
non-stationary mdp
(2)
causal inference
(2)
tail risk
(2)
offline reinforcement learning
(2)
phase transition
(2)
worst-case optimality
(2)
gradient descent
(1)
reproducing kernel hilbert space
(1)
density estimation
(1)
mechanism design
(1)
Papers
Contextual Online Decision Making with Infinite-Dimensional Functional Regression
ICML 2025
Privacy Preserving Adaptive Experiment Design
ICML 2024
Dynamic Service Fee Pricing under Strategic Behavior: Actions as Instruments and Phase Transition
NIPS 2024
Offline Oracle-Efficient Learning for Contextual MDPs via Layerwise Exploration-Exploitation Tradeoff
NIPS 2024
Pricing Experimental Design: Causal Effect, Expected Revenue and Tail Risk
ICML 2023
Non-stationary Experimental Design under Linear Trends
NIPS 2023
Stochastic Multi-armed Bandits: Optimal Trade-off among Optimality, Consistency, and Tail Risk
NIPS 2023
Multi-armed Bandit Experimental Design: Online Decision-making and Adaptive Inference
AISTATS 2023
Sobolev Norm Learning Rates for Conditional Mean Embeddings
AISTATS 2022
Learning Mixed Multinomial Logits with Provable Guarantees
NIPS 2022
Context-Based Dynamic Pricing with Partially Linear Demand Model
NIPS 2022
A Simple and Optimal Policy Design for Online Learning with Safety against Heavy-tailed Risk
NIPS 2022
Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation
COLT 2022
Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective
COLT 2021
Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs
ICML 2021
Dynamic Planning and Learning under Recovering Rewards
ICML 2021
Reaping the Benefits of Bundling under High Production Costs
AISTATS 2021
Online Pricing with Offline Data: Phase Transition and Inverse Square Law
ICML 2020
Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism
ICML 2020
Learning to Optimize under Non-Stationarity
AISTATS 2019
Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints
NIPS 2019
The Lingering of Gradients: How to Reuse Gradients Over Time
NIPS 2018