Emilie Kaufmann
45 papers · 2012–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (16) π§ Keyword Pioneer π£ Hot Topic Early Bird π Conference Polyglot (7)
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(7)
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Academic Marathon
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(11)
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(4)
ποΈ
Keyword Collector
(134)
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Century Club
(45)
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Unstoppable
(10)
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Prolific Year
(5)
Conferences
NIPS (13)
AISTATS (10)
ALT (8)
COLT (5)
ICML (4)
JMLR (4)
UAI (1)
Top co-authors
Research topics
Keywords
multi-armed bandit
(22)
sample complexity
(18)
regret bound
(10)
thompson sampling
(7)
markov decision process
(6)
pure exploration
(5)
best arm identification
(4)
reward-free exploration
(3)
regret minimization
(3)
bayesian inference
(3)
asymptotic optimality
(3)
pac reinforcement learning
(3)
reinforcement learning
(3)
best-arm identification
(3)
posterior distribution
(2)
bandit algorithm
(2)
pareto optimal
(2)
pac learning
(2)
sequential testing
(2)
monte-carlo tree search
(2)
Papers
Best-Arm Identification in Unimodal Bandits
AISTATS 2025
Pareto Set Identification With Posterior Sampling
AISTATS 2025
Bandit Pareto Set Identification in a Multi-Output Linear Model
AISTATS 2025
Constrained Pareto Set Identification with Bandit Feedback
ICML 2025
Bandit Pareto Set Identification: the Fixed Budget Setting
AISTATS 2024
Finding good policies in average-reward Markov Decision Processes without prior knowledge
NIPS 2024
Optimal Multi-Fidelity Best-Arm Identification
NIPS 2024
Power Mean Estimation in Stochastic Monte-Carlo Tree Search
UAI 2024
Active Coverage for PAC Reinforcement Learning
COLT 2023
Optimistic PAC Reinforcement Learning: the Instance-Dependent View
ALT 2023
An $\varepsilon$-Best-Arm Identification Algorithm for Fixed-Confidence and Beyond
NIPS 2023
Adaptive Algorithms for Relaxed Pareto Set Identification
NIPS 2023
Top Two Algorithms Revisited
NIPS 2022
Near-Optimal Collaborative Learning in Bandits
NIPS 2022
Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits
JMLR 2022
Efficient Algorithms for Extreme Bandits
AISTATS 2022
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs
NIPS 2022
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces
AISTATS 2021
Top-m identification for linear bandits
AISTATS 2021
Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited
ALT 2021
Adaptive Reward-Free Exploration
ALT 2021
Optimal Thompson Sampling strategies for support-aware CVaR bandits
ICML 2021
Kernel-Based Reinforcement Learning: A Finite-Time Analysis
ICML 2021
Fast active learning for pure exploration in reinforcement learning
ICML 2021
On Multi-Armed Bandit Designs for Dose-Finding Trials
JMLR 2021
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals
JMLR 2021
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity
NIPS 2020
Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling
ALT 2020
A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players
AISTATS 2020
Fixed-confidence guarantees for Bayesian best-arm identification
AISTATS 2020
Sub-sampling for Efficient Non-Parametric Bandit Exploration
NIPS 2020
General parallel optimization a without metric
ALT 2019
{Multi-Player Bandits Revisited}
ALT 2018
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling
NIPS 2018
Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence
ALT 2018
Corrupt Bandits for Preserving Local Privacy
ALT 2018
Monte-Carlo Tree Search by Best Arm Identification
NIPS 2017
On Explore-Then-Commit strategies
NIPS 2016
Optimal Best Arm Identification with Fixed Confidence
COLT 2016
Maximin Action Identification: A New Bandit Framework for Games
COLT 2016
On the Complexity of Best-Arm Identification in Multi-Armed Bandit Models
JMLR 2016
On the Complexity of A/B Testing
COLT 2014
Thompson Sampling for 1-Dimensional Exponential Family Bandits
NIPS 2013
Information Complexity in Bandit Subset Selection
COLT 2013
On Bayesian Upper Confidence Bounds for Bandit Problems
AISTATS 2012