Aditya Gopalan
23 papers · 2014–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) πΊοΈ Taxonomy Completionist (11) π§ Keyword Pioneer π Interdisciplinary Bridge π Academic Marathon (11)
π
Conference Polyglot
(7)
π
Academic Marathon
(11)
π¬
Deep Specialist
(10)
ποΈ
Keyword Collector
(74)
π
Century Club
(23)
π₯
Unstoppable
(7)
π
Trend Setter
β‘
Prolific Year
(5)
Conferences
AISTATS (8)
ICML (6)
NIPS (3)
AAAI (2)
COLT (2)
ALT (1)
IJCAI (1)
Top co-authors
Keywords
regret bound
(10)
multi-armed bandit
(6)
pac learning
(5)
sample complexity
(4)
active learning
(3)
markov decision process
(3)
bayesian optimization
(3)
best arm identification
(3)
subset selection
(3)
reproducing kernel hilbert space
(3)
preference learning
(3)
gaussian process
(3)
information gain
(2)
upper confidence bound
(2)
linear bandit
(2)
online learning
(2)
plackett-luce model
(2)
exponential family
(2)
thompson sampling
(2)
bandit algorithm
(2)
Papers
Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms
ICML 2025
Testing the Feasibility of Linear Programs with Bandit Feedback
ICML 2024
Model-Based Best Arm Identification for Decreasing Bandits
AISTATS 2024
A Unified Framework for Discovering Discrete Symmetries
AISTATS 2024
Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference
AISTATS 2023
Bregman Deviations of Generic Exponential Families
COLT 2023
Improved Pure Exploration in Linear Bandits with No-Regret Learning
IJCAI 2022
Actor-Critic based Improper Reinforcement Learning
ICML 2022
Bandit Quickest Changepoint Detection
NIPS 2021
No-regret Algorithms for Multi-task Bayesian Optimization
AISTATS 2021
Reinforcement Learning in Parametric MDPs with Exponential Families
AISTATS 2021
Best-item Learning in Random Utility Models with Subset Choices
AISTATS 2020
Sequential Mode Estimation with Oracle Queries
AAAI 2020
On Adaptivity in Information-Constrained Online Learning
AAAI 2020
From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model
ICML 2020
Combinatorial Bandits with Relative Feedback
NIPS 2019
Bayesian Optimization under Heavy-tailed Payoffs
NIPS 2019
Online Learning in Kernelized Markov Decision Processes
AISTATS 2019
PAC Battling Bandits in the Plackett-Luce Model
ALT 2019
Active Ranking with Subset-wise Preferences
AISTATS 2019
On Kernelized Multi-armed Bandits
ICML 2017
Thompson Sampling for Learning Parameterized Markov Decision Processes
COLT 2015
Thompson Sampling for Complex Online Problems
ICML 2014