Branislav Kveton
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
94
Venues
25
Active years
2004–2026
Best venue rank
A*
Where they publish
- A*ICML18 papers
- AAISTATS15 papers
- AUAI14 papers
- A*AAAI11 papers
- A*IJCAI7 papers
- ARecSys3 papers
- AIUI2 papers
- A*ACL2 papers
- A*ICLR2 papers
- AWSDM2 papers
- ACIKM2 papers
- NationalFlAIRS2 papers
- A*WWW2 papers
- AEACL1 paper
- A*EMNLP1 paper
- A*ICCV1 paper
- A*SIGIR1 paper
- AECAI1 paper
- A*KDD1 paper
- A*INFOCOM1 paper
- A*ICDM1 paper
- A*CVPR1 paper
- CIAAI1 paper
- NationalISAIM1 paper
- NationalAMIA1 paper
Papers
94 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | EACL | A Survey on LLM-based Conversational User Simulation. | Bo Ni, Yu Wang, Leyao Wang, Branislav Kveton, Franck Dernoncourt, Yu Xia, Hongjie Chen, Reuben Luera, Samyadeep Basu, Subhojyoti Mukherjee, Puneet Mathur, Nesreen K. Ahmed, Junda Wu, Li Li, Huixin Zhang, Ruiyi Zhang, Tong Yu, Sungchul Kim, Jiuxiang Gu, Zhengzhong Tu, Alexa F. Siu, Zichao Wang, Seunghyun Yoon, Nedim Lipka, Namyong Park, Zihao Lin, Trung Bui, Yue Zhao, Tyler Derr, Ryan A. Rossi |
| 2026 | IUI | Riding the Carousel: The First Extensive Eye Tracking Analysis of Browsing Behavior in Carousel Recommenders. | Santiago de Leon-Martinez, Rbert Mro, Branislav Kveton, Mria Bielikov |
| 2025 | AAAI | Cross-Validated Off-Policy Evaluation. | Matej Cief, Branislav Kveton, Michal Kompan |
| 2025 | AAAI | Selective Uncertainty Propagation in Offline RL. | Sanath Kumar Krishnamurthy, Tanmay Gangwani, Sumeet Katariya, Branislav Kveton, Shrey Modi, Anshuka Rangi |
| 2025 | ACL | GUI Agents: A Survey. | Dang Nguyen, Jian Chen, Yu Wang, Gang Wu, Namyong Park, Zhengmian Hu, Hanjia Lyu, Junda Wu, Ryan Aponte, Yu Xia, Xintong Li, Jing Shi, Hongjie Chen, Viet Dac Lai, Zhouhang Xie, Sungchul Kim, Ruiyi Zhang, Tong Yu, Md. Mehrab Tanjim, Nesreen K. Ahmed, Puneet Mathur, Seunghyun Yoon, Lina Yao, Branislav Kveton, Jihyung Kil, Thien Huu Nguyen, Trung Bui, Tianyi Zhou, Ryan A. Rossi, Franck Dernoncourt |
| 2025 | ACL | From Selection to Generation: A Survey of LLM-based Active Learning. | Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie, Junda Wu, Xintong Li, Ryan Aponte, Hanjia Lyu, Joe Barrow, Hongjie Chen, Franck Dernoncourt, Branislav Kveton, Tong Yu, Ruiyi Zhang, Jiuxiang Gu, Nesreen K. Ahmed, Yu Wang, Xiang Chen, Hanieh Deilamsalehy, Sungchul Kim, Zhengmian Hu, Yue Zhao, Nedim Lipka, Seunghyun Yoon, Ting-Hao 'Kenneth' Huang, Zichao Wang, Puneet Mathur, Soumyabrata Pal, Koyel Mukherjee, Zhehao Zhang, Namyong Park, Thien Huu Nguyen, Jiebo Luo, Ryan A. Rossi, Julian J. McAuley |
| 2025 | EMNLP | LaMP-Cap: Personalized Figure Caption Generation With Multimodal Figure Profiles. | Ho Yin Sam Ng, Edward Hsu, Aashish Anantha Ramakrishnan, Branislav Kveton, Nedim Lipka, Franck Dernoncourt, Dongwon Lee, Tong Yu, Sungchul Kim, Ryan A. Rossi, Ting-Hao 'Kenneth' Huang |
| 2025 | ICCV | Multimodal LLMs as Customized Reward Models for Text-to-Image Generation. | Shijie Zhou, Ruiyi Zhang, Huaisheng Zhu, Branislav Kveton, Yufan Zhou, Jiuxiang Gu, Jian Chen, Changyou Chen |
| 2025 | ICLR | OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models. | Junda Wu, Xintong Li, Ruoyu Wang, Yu Xia, Yuxin Xiong, Jianing Wang, Tong Yu, Xiang Chen, Branislav Kveton, Lina Yao, Jingbo Shang, Julian J. McAuley |
| 2025 | ICML | FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain. | Rohan Deb, Kiran Koshy Thekumparampil, Kousha Kalantari, Gaurush Hiranandani, Shoham Sabach, Branislav Kveton |
| 2025 | ICML | Comparing Few to Rank Many: Active Human Preference Learning Using Randomized Frank-Wolfe Method. | Kiran Koshy Thekumparampil, Gaurush Hiranandani, Kousha Kalantari, Shoham Sabach, Branislav Kveton |
| 2025 | SIGIR | RecGaze: The First Eye Tracking and User Interaction Dataset for Carousel Interfaces. | Santiago de Leon-Martinez, Jingwei Kang, Rbert Mro, Maarten de Rijke, Branislav Kveton, Harrie Oosterhuis, Mria Bielikov |
| 2024 | AISTATS | Pessimistic Off-Policy Multi-Objective Optimization. | Shima Alizadeh, Aniruddha Bhargava, Karthick Gopalswamy, Lalit Jain, Branislav Kveton, Ge Liu |
| 2024 | ECAI | Pessimistic Off-Policy Optimization for Learning to Rank. | Matej Cief, Branislav Kveton, Michal Kompan |
| 2024 | ICLR | Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling. | Aadirupa Saha, Branislav Kveton |
| 2024 | ICML | MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent. | Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher |
| 2024 | WSDM | Pre-trained Recommender Systems: A Causal Debiasing Perspective. | Ziqian Lin, Hao Ding, Trong Nghia Hoang, Branislav Kveton, Anoop Deoras, Hao Wang |
| 2024 | WSDM | Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs. | Behnam Rahdari, Hao Ding, Ziwei Fan, Yifei Ma, Zhuotong Chen, Anoop Deoras, Branislav Kveton |
| 2023 | AAAI | Meta-Learning for Simple Regret Minimization. | Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh, Sumeet Katariya |
| 2023 | AISTATS | Mixed-Effect Thompson Sampling. | Imad Aouali, Branislav Kveton, Sumeet Katariya |
| 2023 | CIKM | Non-Compliant Bandits. | Branislav Kveton, Yi Liu, Johan Matteo Kruijssen, Yisu Nie |
| 2023 | ICML | Multi-Task Off-Policy Learning from Bandit Feedback. | Joey Hong, Branislav Kveton, Manzil Zaheer, Sumeet Katariya, Mohammad Ghavamzadeh |
| 2023 | ICML | Thompson Sampling with Diffusion Generative Prior. | Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blbaum |
| 2023 | ICML | Multiplier Bootstrap-based Exploration. | Runzhe Wan, Haoyu Wei, Branislav Kveton, Rui Song |
| 2023 | RecSys | Trending Now: Modeling Trend Recommendations. | Hao Ding, Branislav Kveton, Yifei Ma, Youngsuk Park, Venkataramana Kini, Yupeng Gu, Ravi Divvela, Fei Wang, Anoop Deoras, Hao Wang |
| 2023 | UAI | Fixed-Budget Best-Arm Identification with Heterogeneous Reward Variances. | Anusha Lalitha, Kousha Kalantari, Yifei Ma, Anoop Deoras, Branislav Kveton |
| 2022 | AISTATS | Hierarchical Bayesian Bandits. | Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh |
| 2022 | AISTATS | Thompson Sampling with a Mixture Prior. | Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier |
| 2022 | AISTATS | On the Value of Prior in Online Learning to Rank. | Branislav Kveton, Ofer Meshi, Masrour Zoghi, Zhen Qin |
| 2022 | AISTATS | Safe Optimal Design with Applications in Off-Policy Learning. | Ruihao Zhu, Branislav Kveton |
| 2022 | AISTATS | Random Effect Bandits. | Rong Zhu, Branislav Kveton |
| 2022 | FlAIRS | Towards Increasing the Coverage of Interactive Recommendations. | Behnam Rahdari, Peter Brusilovsky, Branislav Kveton |
| 2022 | ICML | Deep Hierarchy in Bandits. | Joey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh |
| 2022 | ICML | Safe Exploration for Efficient Policy Evaluation and Comparison. | Runzhe Wan, Branislav Kveton, Rui Song |
| 2022 | IJCAI | Fixed-Budget Best-Arm Identification in Structured Bandits. | Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh |
| 2022 | IJCAI | IMO^3: Interactive Multi-Objective Off-Policy Optimization. | Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton, Craig Boutilier |
| 2021 | AISTATS | Non-Stationary Off-Policy Optimization. | Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed |
| 2021 | ICML | Meta-Thompson Sampling. | Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvri |
| 2021 | UAI | CORe: Capitalizing On Rewards in Bandit Exploration. | Nan Wang, Branislav Kveton, Maryam Karimzadehgan |
| 2020 | AISTATS | Randomized Exploration in Generalized Linear Bandits. | Branislav Kveton, Manzil Zaheer, Csaba Szepesvri, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier |
| 2020 | AISTATS | Old Dog Learns New Tricks: Randomized UCB for Bandit Problems. | Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton |
| 2020 | ICML | Graphical Models Meet Bandits: A Variational Thompson Sampling Approach. | Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel |
| 2019 | AISTATS | Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit. | Yang Cao, Zheng Wen, Branislav Kveton, Yao Xie |
| 2019 | AISTATS | Conservative Exploration using Interleaving. | Sumeet Katariya, Branislav Kveton, Zheng Wen, Vamsi K. Potluru |
| 2019 | AISTATS | Sample Efficient Graph-Based Optimization with Noisy Observations. | Thanh Tan Nguyen, Ali Shameli, Yasin Abbasi-Yadkori, Anup Rao, Branislav Kveton |
| 2019 | ICML | Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits. | Branislav Kveton, Csaba Szepesvri, Sharan Vaswani, Zheng Wen, Tor Lattimore, Mohammad Ghavamzadeh |
| 2019 | IJCAI | Perturbed-History Exploration in Stochastic Multi-Armed Bandits. | Branislav Kveton, Csaba Szepesvri, Mohammad Ghavamzadeh, Craig Boutilier |
| 2019 | UAI | BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback. | Chang Li, Branislav Kveton, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvri, Masrour Zoghi |
| 2019 | UAI | Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank. | Gaurush Hiranandani, Harvineet Singh, Prakhar Gupta, Iftikhar Ahamath Burhanuddin, Zheng Wen, Branislav Kveton |
| 2019 | UAI | Perturbed-History Exploration in Stochastic Linear Bandits. | Branislav Kveton, Csaba Szepesvri, Mohammad Ghavamzadeh, Craig Boutilier |
| 2018 | CIKM | Predictive Analysis by Leveraging Temporal User Behavior and User Embeddings. | Charles Chen, Sungchul Kim, Hung Bui, Ryan A. Rossi, Eunyee Koh, Branislav Kveton, Razvan C. Bunescu |
| 2018 | KDD | Offline Evaluation of Ranking Policies with Click Models. | Shuai Li, Yasin Abbasi-Yadkori, Branislav Kveton, S. Muthukrishnan, Vishwa Vinay, Zheng Wen |
| 2018 | RecSys | Efficient online recommendation via low-rank ensemble sampling. | Xiuyuan Lu, Zheng Wen, Branislav Kveton |
| 2018 | WWW | Finding Subcube Heavy Hitters in Analytics Data Streams. | Branislav Kveton, S. Muthukrishnan, Hoa T. Vu, Yikun Xian |
| 2017 | AISTATS | Stochastic Rank-1 Bandits. | Sumeet Katariya, Branislav Kveton, Csaba Szepesvri, Claire Vernade, Zheng Wen |
| 2017 | ICML | Model-Independent Online Learning for Influence Maximization. | Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt |
| 2017 | ICML | Online Learning to Rank in Stochastic Click Models. | Masrour Zoghi, Toms Tunys, Mohammad Ghavamzadeh, Branislav Kveton, Csaba Szepesvri, Zheng Wen |
| 2017 | IJCAI | Bernoulli Rank-1 Bandits for Click Feedback. | Sumeet Katariya, Branislav Kveton, Csaba Szepesvri, Claire Vernade, Zheng Wen |
| 2017 | WWW | Does Weather Matter?: Causal Analysis of TV Logs. | Shi Zong, Branislav Kveton, Shlomo Berkovsky, Azin Ashkan, Nikos Vlassis, Zheng Wen |
| 2016 | ICML | DCM Bandits: Learning to Rank with Multiple Clicks. | Sumeet Katariya, Branislav Kveton, Csaba Szepesvri, Zheng Wen |
| 2016 | IJCAI | Practical Linear Models for Large-Scale One-Class Collaborative Filtering. | Suvash Sedhain, Hung Bui, Jaya Kawale, Nikos Vlassis, Branislav Kveton, Aditya Krishna Menon, Trung Bui, Scott Sanner |
| 2016 | UAI | Cascading Bandits for Large-Scale Recommendation Problems. | Shi Zong, Hao Ni, Kenny Sung, Nan Rosemary Ke, Zheng Wen, Branislav Kveton |
| 2015 | AISTATS | Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits. | Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvri |
| 2015 | ICML | Cascading Bandits: Learning to Rank in the Cascade Model. | Branislav Kveton, Csaba Szepesvri, Zheng Wen, Azin Ashkan |
| 2015 | ICML | Efficient Learning in Large-Scale Combinatorial Semi-Bandits. | Zheng Wen, Branislav Kveton, Azin Ashkan |
| 2015 | IJCAI | Optimal Greedy Diversity for Recommendation. | Azin Ashkan, Branislav Kveton, Shlomo Berkovsky, Zheng Wen |
| 2015 | IUI | Minimal Interaction Search in Recommender Systems. | Branislav Kveton, Shlomo Berkovsky |
| 2014 | AAAI | Large-Scale Optimistic Adaptive Submodularity. | Victor Gabillon, Branislav Kveton, Zheng Wen, Brian Eriksson, S. Muthukrishnan |
| 2014 | ICML | Spectral Bandits for Smooth Graph Functions. | Michal Valko, Rmi Munos, Branislav Kveton, Toms Kock |
| 2014 | RecSys | Diversified Utility Maximization for Recommendations. | Azin Ashkan, Branislav Kveton, Shlomo Berkovsky, Zheng Wen |
| 2014 | UAI | Matroid Bandits: Fast Combinatorial Optimization with Learning. | Branislav Kveton, Zheng Wen, Azin Ashkan, Hoda Eydgahi, Brian Eriksson |
| 2014 | UAI | SPPM: Sparse Privacy Preserving Mappings. | Salman Salamatian, Nadia Fawaz, Branislav Kveton, Nina Taft |
| 2013 | AAAI | Structured Kernel-Based Reinforcement Learning. | Branislav Kveton, Georgios Theocharous |
| 2013 | ICML | Sequential Bayesian Search. | Zheng Wen, Branislav Kveton, Brian Eriksson, Sandilya Bhamidipati |
| 2013 | INFOCOM | Predicting user dissatisfaction with Internet application performance at end-hosts. | Diana Joumblatt, Jaideep Chandrashekar, Branislav Kveton, Nina Taft, Renata Teixeira |
| 2012 | AAAI | Kernel-Based Reinforcement Learning on Representative States. | Branislav Kveton, Georgios Theocharous |
| 2012 | UAI | Leveraging Side Observations in Stochastic Bandits. | Stphane Caron, Branislav Kveton, Marc Lelarge, Smriti Bhagat |
| 2012 | UAI | Incorporating Metadata into Dynamic Topic Analysis. | Tianxi Li, Branislav Kveton, Yu Wu, Ashwin Kashyap |
| 2011 | AAAI | Automatic Identity Inference for Smart TVs. | Avneesh Singh Saluja, Frank Mokaya, Mariano Phielipp, Branislav Kveton |
| 2011 | ICDM | Conditional Anomaly Detection with Soft Harmonic Functions. | Michal Valko, Branislav Kveton, Hamed Valizadegan, Gregory F. Cooper, Milos Hauskrecht |
| 2010 | CVPR | Online semi-supervised perception: Real-time learning without explicit feedback. | Branislav Kveton, Matthai Philipose, Michal Valko, Ling Huang |
| 2010 | IAAI | Fast, Accurate, and Practical Identity Inference Using TV Remote Controls. | Mariano Phielipp, Magdiel Galan, Richard Lee, Branislav Kveton, Jeffrey Hightower |
| 2010 | UAI | Online Semi-Supervised Learning on Quantized Graphs. | Michal Valko, Branislav Kveton, Ling Huang, Daniel Ting |
| 2010 | UAI | Automatic Tuning of Interactive Perception Applications. | Qian Zhu, Branislav Kveton, Lily B. Mummert, Padmanabhan Pillai |
| 2008 | AAAI | Online Learning with Expert Advice and Finite-Horizon Constraints. | Branislav Kveton, Jia Yuan Yu, Georgios Theocharous, Shie Mannor |
| 2008 | ISAIM | A Lazy Approach to Online Learning with Constraints. | Branislav Kveton, Jia Yuan Yu, Georgios Theocharous, Shie Mannor |
| 2008 | UAI | Partitioned Linear Programming Approximations for MDPs. | Branislav Kveton, Milos Hauskrecht |
| 2007 | AAAI | Adaptive Timeout Policies for Fast Fine-Grained Power Management. | Branislav Kveton, Prashant Gandhi, Georgios Theocharous, Shie Mannor, Barbara Rosario, Nilesh Shah |
| 2007 | AMIA | Evidence-based Anomaly Detection in Clinical Domains. | Milos Hauskrecht, Michal Valko, Branislav Kveton, Shyam Visweswaran, Gregory F. Cooper |
| 2006 | AAAI | When Gossip is Good: Distributed Probabilistic Inference for Detection of Slow Network Intrusions. | Denver Dash, Branislav Kveton, John Mark Agosta, Eve M. Schooler, Jaideep Chandrashekar, Abraham Bachrach, Alex Newman |
| 2006 | AAAI | Learning Basis Functions in Hybrid Domains. | Branislav Kveton, Milos Hauskrecht |
| 2005 | FlAIRS | Automatic Excursion Detection in Manufacturing: Preliminary Results. | Branislav Kveton, Denver Dash |
| 2005 | IJCAI | An MCMC Approach to Solving Hybrid Factored MDPs. | Branislav Kveton, Milos Hauskrecht |
| 2004 | UAI | Solving Factored MDPs with Continuous and Discrete Variables. | Carlos Guestrin, Milos Hauskrecht, Branislav Kveton |