Shipra Agrawal
20 papers · 2012–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π Conference Polyglot (8) πΊοΈ Taxonomy Completionist (13) π§ Keyword Pioneer π Academic Marathon (13)
π
Interdisciplinary Bridge
π
Conference Polyglot
(8)
π
Academic Marathon
(13)
ποΈ
Keyword Collector
(65)
π
Trend Setter
π
Century Club
(20)
π
Conference Pioneer
Conferences
COLT (5)
ICML (4)
NIPS (4)
ALT (3)
AAAI (1)
AISTATS (1)
IJCAI (1)
JMLR (1)
Top co-authors
Keywords
regret bound
(10)
thompson sampling
(5)
multi-armed bandit
(5)
bayesian inference
(4)
online learning
(4)
contextual bandit
(3)
reinforcement learning
(3)
regret minimization
(2)
deep reinforcement learning
(2)
online algorithm
(2)
stochastic optimization
(2)
markov decision process
(1)
mechanism design
(1)
distributional reinforcement learning
(1)
deep learning
(1)
integer programming
(1)
posterior sampling
(1)
continuous control
(1)
exploration exploitation
(1)
bipartite matching
(1)
Papers
Data Dependent Regret Bounds for Online Portfolio Selection with Predicted Returns
ALT 2025
Optimistic Q-learning for average reward and episodic reinforcement learning extended abstract
COLT 2025
Conference on Learning Theory 2024: Preface
COLT 2024
Dynamic Pricing and Learning with Bayesian Persuasion
NIPS 2023
Algorithmic Learning Theory 2023: Preface
ALT 2023
Online Allocation and Learning in the Presence of Strategic Agents
NIPS 2022
Scale-Free Adversarial Multi Armed Bandits
ALT 2022
Reinforcement Learning for Integer Programming: Learning to Cut
ICML 2020
Discretizing Continuous Action Space for On-Policy Optimization
AAAI 2020
Spectral bandits
JMLR 2020
Exploration by Distributional Reinforcement Learning
IJCAI 2018
Bandits with Delayed, Aggregated Anonymous Feedback
ICML 2018
Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy
ICML 2018
Optimistic posterior sampling for reinforcement learning: worst-case regret bounds
NIPS 2017
Thompson Sampling for the MNL-Bandit
COLT 2017
An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives
COLT 2016
Linear Contextual Bandits with Knapsacks
NIPS 2016
Thompson Sampling for Contextual Bandits with Linear Payoffs
ICML 2013
Further Optimal Regret Bounds for Thompson Sampling
AISTATS 2013
Analysis of Thompson Sampling for the Multi-armed Bandit Problem
COLT 2012