Branislav Kveton

Orcid: 0000-0002-3965-1367

According to our database1, Branislav Kveton authored at least 147 papers between 2003 and 2024.

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Bibliography

2024
Towards Simulation-Based Evaluation of Recommender Systems with Carousel Interfaces.
Trans. Recomm. Syst., March, 2024

Online Posterior Sampling with a Diffusion Prior.
CoRR, 2024

Off-Policy Evaluation from Logged Human Feedback.
CoRR, 2024

Cross-Validated Off-Policy Evaluation.
CoRR, 2024

Optimal Design for Human Feedback.
CoRR, 2024

Experimental Design for Active Transductive Inference in Large Language Models.
CoRR, 2024

Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Pre-trained Recommender Systems: A Causal Debiasing Perspective.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Pessimistic Off-Policy Optimization for Learning to Rank.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Pessimistic Off-Policy Multi-Objective Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Pre-trained Recommender Systems: A Causal Debiasing Perspective.
CoRR, 2023

Efficient and Interpretable Bandit Algorithms.
CoRR, 2023

Selective Uncertainty Propagation in Offline RL.
CoRR, 2023

Fixed-Budget Best-Arm Identification with Heterogeneous Reward Variances.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Towards Sequential Counterfactual Learning to Rank.
Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, 2023

Trending Now: Modeling Trend Recommendations.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Logarithmic Bayes Regret Bounds.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multiplier Bootstrap-based Exploration.
Proceedings of the International Conference on Machine Learning, 2023

Thompson Sampling with Diffusion Generative Prior.
Proceedings of the International Conference on Machine Learning, 2023

Multi-Task Off-Policy Learning from Bandit Feedback.
Proceedings of the International Conference on Machine Learning, 2023

Non-Compliant Bandits.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Mixed-Effect Thompson Sampling.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Meta-Learning for Simple Regret Minimization.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Bayesian Fixed-Budget Best-Arm Identification.
CoRR, 2022

Robust Contextual Linear Bandits.
CoRR, 2022

From Ranked Lists to Carousels: A Carousel Click Model.
CoRR, 2022

Generalizing Hierarchical Bayesian Bandits.
CoRR, 2022

IMO<sup>3</sup>: Interactive Multi-Objective Off-Policy Optimization.
CoRR, 2022

Optimal probing with statistical guarantees for network monitoring at scale.
Comput. Commun., 2022

Uplifting Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

IMO^3: Interactive Multi-Objective Off-Policy Optimization.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Fixed-Budget Best-Arm Identification in Structured Bandits.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Safe Exploration for Efficient Policy Evaluation and Comparison.
Proceedings of the International Conference on Machine Learning, 2022

Deep Hierarchy in Bandits.
Proceedings of the International Conference on Machine Learning, 2022

The Magic of Carousels: Single vs. Multi-List Recommender Systems.
Proceedings of the HT '22: 33rd ACM Conference on Hypertext and Social Media, 2022

Towards Increasing the Coverage of Interactive Recommendations.
Proceedings of the Thirty-Fifth International Florida Artificial Intelligence Research Society Conference, 2022

Random Effect Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Safe Optimal Design with Applications in Off-Policy Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

On the Value of Prior in Online Learning to Rank.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Thompson Sampling with a Mixture Prior.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Hierarchical Bayesian Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Safe Optimal Design with Applications in Policy Learning.
CoRR, 2021

Fixed-Budget Best-Arm Identification in Contextual Bandits: A Static-Adaptive Algorithm.
CoRR, 2021

CORe: Capitalizing On Rewards in Bandit Exploration.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

No Regrets for Learning the Prior in Bandits.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Meta-Thompson Sampling.
Proceedings of the 38th International Conference on Machine Learning, 2021

Non-Stationary Off-Policy Optimization.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Non-Stationary Latent Bandits.
CoRR, 2020

Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems.
CoRR, 2020

Piecewise-Stationary Off-Policy Optimization.
CoRR, 2020

Differentiable Meta-Learning in Contextual Bandits.
CoRR, 2020

Differentiable Bandit Exploration.
CoRR, 2020

Latent Bandits Revisited.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Differentiable Meta-Learning of Bandit Policies.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Graphical Models Meet Bandits: A Variational Thompson Sampling Approach.
Proceedings of the 37th International Conference on Machine Learning, 2020

Old Dog Learns New Tricks: Randomized UCB for Bandit Problems.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Randomized Exploration in Generalized Linear Bandits.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Waterfall Bandits: Learning to Sell Ads Online.
CoRR, 2019

Empirical Bayes Regret Minimization.
CoRR, 2019

Perturbed-History Exploration in Stochastic Linear Bandits.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Perturbed-History Exploration in Stochastic Multi-Armed Bandits.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits.
Proceedings of the 36th International Conference on Machine Learning, 2019

Sample Efficient Graph-Based Optimization with Noisy Observations.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Conservative Exploration using Interleaving.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits.
CoRR, 2018

Online Diverse Learning to Rank from Partial-Click Feedback.
CoRR, 2018

BubbleRank: Safe Online Learning to Rerank.
CoRR, 2018

New Insights into Bootstrapping for Bandits.
CoRR, 2018

Nearly Optimal Adaptive Procedure for Piecewise-Stationary Bandit: a Change-Point Detection Approach.
CoRR, 2018

Finding Subcube Heavy Hitters in Analytics Data Streams.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Efficient online recommendation via low-rank ensemble sampling.
Proceedings of the 12th ACM Conference on Recommender Systems, 2018

SpectralLeader: Online Spectral Learning for Single Topic Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

TopRank: A practical algorithm for online stochastic ranking.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Offline Evaluation of Ranking Policies with Click Models.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Predictive Analysis by Leveraging Temporal User Behavior and User Embeddings.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017
Stochastic Low-Rank Bandits.
CoRR, 2017

SpectralFPL: Online Spectral Learning for Single Topic Models.
CoRR, 2017

Finding Subcube Heavy Hitters in Data Streams.
CoRR, 2017

Diffusion Independent Semi-Bandit Influence Maximization.
CoRR, 2017

Does Weather Matter?: Causal Analysis of TV Logs.
Proceedings of the 26th International Conference on World Wide Web Companion, 2017

Get to the Bottom: Causal Analysis for User Modeling.
Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 2017

Thompson Sampling for Optimizing Stochastic Local Search.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Bernoulli Rank-1 Bandits for Click Feedback.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Online Learning to Rank in Stochastic Click Models.
Proceedings of the 34th International Conference on Machine Learning, 2017

Model-Independent Online Learning for Influence Maximization.
Proceedings of the 34th International Conference on Machine Learning, 2017

Stochastic Rank-1 Bandits.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Minimal Interaction Content Discovery in Recommender Systems.
ACM Trans. Interact. Intell. Syst., 2016

Influence Maximization with Semi-Bandit Feedback.
CoRR, 2016

Cascading Bandits for Large-Scale Recommendation Problems.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Graphical Model Sketch.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Practical Linear Models for Large-Scale One-Class Collaborative Filtering.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

DCM Bandits: Learning to Rank with Multiple Clicks.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
PriView: Personalized Media Consumption Meets Privacy against Inference Attacks.
IEEE Softw., 2015

Managing Your Private and Public Data: Bringing Down Inference Attacks Against Your Privacy.
IEEE J. Sel. Top. Signal Process., 2015

Cascading Bandits.
CoRR, 2015

Combinatorial Cascading Bandits.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Efficient Thompson Sampling for Online Matrix-Factorization Recommendation.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Minimal Interaction Search in Recommender Systems.
Proceedings of the 20th International Conference on Intelligent User Interfaces, 2015

Optimal Greedy Diversity for Recommendation.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Efficient Learning in Large-Scale Combinatorial Semi-Bandits.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Cascading Bandits: Learning to Rank in the Cascade Model.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Efficient Learning in Large-Scale Combinatorial Semi-Bandits.
CoRR, 2014

Learning to Act Greedily: Polymatroid Semi-Bandits.
CoRR, 2014

DUM: Diversity-Weighted Utility Maximization for Recommendations.
CoRR, 2014

SPPM: Sparse Privacy Preserving Mappings.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Matroid Bandits: Fast Combinatorial Optimization with Learning.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Diversified Utility Maximization for Recommendations.
Proceedings of the Poster Proceedings of the 8th ACM Conference on Recommender Systems, 2014

Spectral Bandits for Smooth Graph Functions.
Proceedings of the 31th International Conference on Machine Learning, 2014

Large-Scale Optimistic Adaptive Submodularity.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Adaptive Submodular Maximization in Bandit Setting.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Predicting user dissatisfaction with Internet application performance at end-hosts.
Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14-19, 2013, 2013

Sequential Bayesian Search.
Proceedings of the 30th International Conference on Machine Learning, 2013

How to hide the elephant- or the donkey- in the room: Practical privacy against statistical inference for large data.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Learning from a single labeled face and a stream of unlabeled data.
Proceedings of the 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, 2013

Structured Kernel-Based Reinforcement Learning.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012
Incorporating Metadata into Dynamic Topic Analysis.
Proceedings of the Ninth UAI Bayesian Modeling Applications Workshop, 2012

Leveraging Side Observations in Stochastic Bandits.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Kernel-Based Reinforcement Learning on Representative States.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
Conditional Anomaly Detection with Soft Harmonic Functions.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Automatic Identity Inference for Smart TVs.
Proceedings of the Lifelong Learning, 2011

2010
Semi-Supervised Learning with Max-Margin Graph Cuts.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Automatic Tuning of Interactive Perception Applications.
Proceedings of the UAI 2010, 2010

Online Semi-Supervised Learning on Quantized Graphs.
Proceedings of the UAI 2010, 2010

Fast, Accurate, and Practical Identity Inference Using TV Remote Controls.
Proceedings of the Twenty-Second Conference on Innovative Applications of Artificial Intelligence, 2010

Online semi-supervised perception: Real-time learning without explicit feedback.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009
Inferring Identity Using Accelerometers in Television Remote Controls.
Proceedings of the Pervasive Computing, 7th International Conference, 2009

2008
Partitioned Linear Programming Approximations for MDPs.
Proceedings of the UAI 2008, 2008

A Lazy Approach to Online Learning with Constraints.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2008

Online Learning with Expert Advice and Finite-Horizon Constraints.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Evidence-based Anomaly Detection in Clinical Domains.
Proceedings of the AMIA 2007, 2007

Adaptive Timeout Policies for Fast Fine-Grained Power Management.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Solving Factored MDPs with Hybrid State and Action Variables.
J. Artif. Intell. Res., 2006

Solving Factored MDPs with Exponential-Family Transition Models.
Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling, 2006

Learning Basis Functions in Hybrid Domains.
Proceedings of the Proceedings, 2006

When Gossip is Good: Distributed Probabilistic Inference for Detection of Slow Network Intrusions.
Proceedings of the Proceedings, 2006

2005
An MCMC Approach to Solving Hybrid Factored MDPs.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Automatic Excursion Detection in Manufacturing: Preliminary Results.
Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, 2005

2004
Solving Factored MDPs with Continuous and Discrete Variables.
Proceedings of the UAI '04, 2004

Heuristic Refinements of Approximate Linear Programming for Factored Continuous-State Markov Decision Processes.
Proceedings of the Fourteenth International Conference on Automated Planning and Scheduling (ICAPS 2004), 2004

2003
Linear Program Approximations for Factored Continuous-State Markov Decision Processes.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003


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