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Branislav Kveton

68 papers · 2010–2026 · 12 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (30) πŸƒ Academic Marathon (15) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (11) 🐝 Cross-Pollinator (11) πŸ”¬ Deep Specialist (24) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ‘₯ Mega-Team (34) 🀝 Dynamic Duo (18) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (13) πŸ—ƒοΈ Keyword Collector (73) πŸ’Ž Century Club (67) ⚑ Prolific Year (10)

Conferences

ICML (18) AISTATS (16) NIPS (12) IJCAI (6) UAI (5) AAAI (3) ACL (2) ICLR (2) EACL (1) EMNLP (1) ICCV (1) JMLR (1)

Top co-authors

Zheng Wen (18) Csaba SzepesvΓ‘ri (16) Mohammad Ghavamzadeh (12) Sumeet Katariya (10) Manzil Zaheer (10) Craig Boutilier (8) Tong Yu (6) Joey Hong (6) Ruiyi Zhang (5) Azin Ashkan (5)

Keywords

regret bound (28) multi-armed bandit (26) thompson sampling (15) online learning (15) learning to rank (6) bayesian inference (5) contextual bandit (5) ucb algorithm (5) bandit algorithm (5) regret minimization (5) bayesian optimization (4) off-policy learning (4) exploration strategy (4) stochastic optimization (4) click model (4) bandit problem (3) linear bandit (3) upper confidence bound (3) cumulative regret (3) posterior sampling (3)

Papers

A Survey on LLM-based Conversational User Simulation EACL 2026
Comparing Few to Rank Many: Active Human Preference Learning Using Randomized Frank-Wolfe Method ICML 2025
Selective Uncertainty Propagation in Offline RL AAAI 2025
Cross-Validated Off-Policy Evaluation AAAI 2025
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain ICML 2025
LaMP-Cap: Personalized Figure Caption Generation With Multimodal Figure Profiles EMNLP 2025
OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models ICLR 2025
GUI Agents: A Survey ACL 2025
Multimodal LLMs as Customized Reward Models for Text-to-Image Generation ICCV 2025
From Selection to Generation: A Survey of LLM-based Active Learning ACL 2025
Online Posterior Sampling with a Diffusion Prior NIPS 2024
MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent ICML 2024
Optimal Design for Human Preference Elicitation NIPS 2024
Pessimistic Off-Policy Multi-Objective Optimization AISTATS 2024
Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling ICLR 2024
Finite-Time Logarithmic Bayes Regret Upper Bounds NIPS 2023
Thompson Sampling with Diffusion Generative Prior ICML 2023
Multi-Task Off-Policy Learning from Bandit Feedback ICML 2023
Multiplier Bootstrap-based Exploration ICML 2023
Mixed-Effect Thompson Sampling AISTATS 2023
Fixed-Budget Best-Arm Identification with Heterogeneous Reward Variances UAI 2023
Meta-Learning for Simple Regret Minimization AAAI 2023
Safe Optimal Design with Applications in Off-Policy Learning AISTATS 2022
Uplifting Bandits NIPS 2022
Random Effect Bandits AISTATS 2022
On the Value of Prior in Online Learning to Rank AISTATS 2022
Thompson Sampling with a Mixture Prior AISTATS 2022
Hierarchical Bayesian Bandits AISTATS 2022
Deep Hierarchy in Bandits ICML 2022
Safe Exploration for Efficient Policy Evaluation and Comparison ICML 2022
Fixed-Budget Best-Arm Identification in Structured Bandits IJCAI 2022
IMO^3: Interactive Multi-Objective Off-Policy Optimization IJCAI 2022
Meta-Thompson Sampling ICML 2021
Non-Stationary Off-Policy Optimization AISTATS 2021
No Regrets for Learning the Prior in Bandits NIPS 2021
CORe: Capitalizing On Rewards in Bandit Exploration UAI 2021
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems AISTATS 2020
Graphical Models Meet Bandits: A Variational Thompson Sampling Approach ICML 2020
Latent Bandits Revisited NIPS 2020
Differentiable Meta-Learning of Bandit Policies NIPS 2020
Randomized Exploration in Generalized Linear Bandits AISTATS 2020
Spectral bandits JMLR 2020
Perturbed-History Exploration in Stochastic Multi-Armed Bandits IJCAI 2019
Conservative Exploration using Interleaving AISTATS 2019
Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank UAI 2019
Perturbed-History Exploration in Stochastic Linear Bandits UAI 2019
Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit AISTATS 2019
Sample Efficient Graph-Based Optimization with Noisy Observations AISTATS 2019
BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback UAI 2019
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits ICML 2019
TopRank: A practical algorithm for online stochastic ranking NIPS 2018
Bernoulli Rank-1 Bandits for Click Feedback IJCAI 2017
Online Learning to Rank in Stochastic Click Models ICML 2017
Model-Independent Online Learning for Influence Maximization ICML 2017
Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback NIPS 2017
Stochastic Rank-1 Bandits AISTATS 2017
DCM Bandits: Learning to Rank with Multiple Clicks ICML 2016
Practical Linear Models for Large-Scale One-Class Collaborative Filtering IJCAI 2016
Optimal Greedy Diversity for Recommendation IJCAI 2015
Efficient Thompson Sampling for Online οΏΌMatrix-Factorization Recommendation NIPS 2015
Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits AISTATS 2015
Cascading Bandits: Learning to Rank in the Cascade Model ICML 2015
Efficient Learning in Large-Scale Combinatorial Semi-Bandits ICML 2015
Combinatorial Cascading Bandits NIPS 2015
Spectral Bandits for Smooth Graph Functions ICML 2014
Adaptive Submodular Maximization in Bandit Setting NIPS 2013
Sequential Bayesian Search ICML 2013
Semi-Supervised Learning with Max-Margin Graph Cuts AISTATS 2010