Branislav Kveton

237 papers A* 51A 39B 1C 1Misc 4Journal 119Unranked 22

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	A Survey on LLM-based Conversational User Simulation. EACL (Volume 1: Long Papers) 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	J	`jnl`	Agentic Planning with Reasoning for Image Styling via Offline RL. CoRR Subhojyoti Mukherjee, Stefano Petrangeli, Branislav Kveton, Trung Bui, Franck Dernoncourt, Arko Mukherjee
2026	J	`jnl`	Human-Aligned MLLM Judges for Fine-Grained Image Editing Evaluation: A Benchmark, Framework, and Analysis. CoRR Runzhou Liu, Hailey Weingord, Sejal Mittal, Prakhar Dungarwal, Anusha Nandula, Bo Ni, Samyadeep Basu, Hongjie Chen, Nesreen K. Ahmed, Li Li, Jiayi Zhang, Koustava Goswami, Subhojyoti Mukherjee, Branislav Kveton, Puneet Mathur, Franck Dernoncourt, Yue Zhao, Yu Wang, Ryan A. Rossi, Zhengzhong Tu, Hongru Du
2026	J	`jnl`	LLM-as-Judge on a Budget. CoRR Aadirupa Saha, Aniket Wagde, Branislav Kveton
2026	J	`jnl`	Partial Policy Gradients for RL in LLMs. CoRR Puneet Mathur, Branislav Kveton, Subhojyoti Mukherjee, Viet Dac Lai
2026	J	`jnl`	Reasoning-Based Personalized Generation for Users with Sparse Data. CoRR Bo Ni, Branislav Kveton, Samyadeep Basu, Subhojyoti Mukherjee, Leyao Wang, Franck Dernoncourt, Sungchul Kim, Seunghyun Yoon, Zichao Wang, Ruiyi Zhang, Puneet Mathur, Jihyung Kil, Jiuxiang Gu, Nedim Lipka, Yu Wang, Ryan A. Rossi, Tyler Derr
2026	A	`conf`	Riding the Carousel: The First Extensive Eye Tracking Analysis of Browsing Behavior in Carousel Recommenders. IUI Santiago de Leon-Martinez, Róbert Móro, Branislav Kveton, Mária Bieliková
2026	J	`jnl`	Stepwise Credit Assignment for GRPO on Flow-Matching Models. CoRR Yash Savani, Branislav Kveton, Yuchen Liu, Yilin Wang, Jing Shi, Subhojyoti Mukherjee, Nikos Vlassis, Krishna Kumar Singh
2025	J	`jnl`	A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations. CoRR Li Li, Peilin Cai, Ryan A. Rossi, Franck Dernoncourt, Branislav Kveton, Junda Wu, Tong Yu, Linxin Song, Tiankai Yang, Yuehan Qin, Nesreen K. Ahmed, Samyadeep Basu, Subhojyoti Mukherjee, Ruiyi Zhang, Zhengmian Hu, Bo Ni, Yuxiao Zhou, Zichao Wang, Yue Huang, Yu Wang, Xiangliang Zhang, Philip S. Yu, Xiyang Hu, Yue Zhao
2025	J	`jnl`	Active Learning for Direct Preference Optimization. CoRR Branislav Kveton, Xintong Li, Julian J. McAuley, Ryan A. Rossi, Jingbo Shang, Junda Wu, Tong Yu
2025	J	`jnl`	An Efficient Plugin Method for Metric Optimization of Black-Box Models. CoRR Siddartha Devic, Nurendra Choudhary, Anirudh Srinivasan, Sahika Genc, Branislav Kveton, Gaurush Hiranandani
2025	A*	`conf`	Comparing Few to Rank Many: Active Human Preference Learning Using Randomized Frank-Wolfe Method. ICML Kiran Koshy Thekumparampil, Gaurush Hiranandani, Kousha Kalantari, Shoham Sabach, Branislav Kveton
2025	A*	`conf`	Cross-Validated Off-Policy Evaluation. AAAI Matej Cief, Branislav Kveton, Michal Kompan
2025	A*	`conf`	FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain. ICML Rohan Deb, Kiran Koshy Thekumparampil, Kousha Kalantari, Gaurush Hiranandani, Shoham Sabach, Branislav Kveton
2025	J	`jnl`	FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain. CoRR Rohan Deb, Kiran Koshy Thekumparampil, Kousha Kalantari, Gaurush Hiranandani, Shoham Sabach, Branislav Kveton
2025	—	`conf`	From Selection to Generation: A Survey of LLM-based Active Learning. ACL (1) 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	J	`jnl`	From Selection to Generation: A Survey of LLM-based Active Learning. CoRR 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	—	`conf`	GUI Agents: A Survey. ACL (Findings) 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	—	`conf`	LaMP-Cap: Personalized Figure Caption Generation With Multimodal Figure Profiles. EMNLP (Findings) 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	J	`jnl`	LaMP-Cap: Personalized Figure Caption Generation With Multimodal Figure Profiles. CoRR Ho Yin Sam Ng, Ting-Yao Hsu, Aashish Anantha Ramakrishnan, Branislav Kveton, Nedim Lipka, Franck Dernoncourt, Dongwon Lee, Tong Yu, Sungchul Kim, Ryan A. Rossi, Ting-Hao Kenneth Huang
2025	J	`jnl`	Learning to Clarify by Reinforcement Learning Through Reward-Weighted Fine-Tuning. CoRR Subhojyoti Mukherjee, Viet Dac Lai, Raghavendra Addanki, Ryan A. Rossi, Seunghyun Yoon, Trung Bui, Anup B. Rao, Jayakumar Subramanian, Branislav Kveton
2025	J	`jnl`	Learning to Reason in LLMs by Expectation Maximization. CoRR Junghyun Lee, Branislav Kveton, Sunav Choudhary, Subhojyoti Mukherjee, Anup B. Rao, Ryan A. Rossi, Alexa Siu
2025	J	`jnl`	ML-Tool-Bench: Tool-Augmented Planning for ML Tasks. CoRR Yaswanth Chittepu, Raghavendra Addanki, Tung Mai, Anup B. Rao, Branislav Kveton
2025	J	`jnl`	MLLM as a UI Judge: Benchmarking Multimodal LLMs for Predicting Human Perception of User Interfaces. CoRR Reuben Luera, Ryan A. Rossi, Franck Dernoncourt, Samyadeep Basu, Sungchul Kim, Subhojyoti Mukherjee, Puneet Mathur, Ruiyi Zhang, Jihyung Kil, Nedim Lipka, Seunghyun Yoon, Jiuxiang Gu, Zichao Wang, Cindy Xiong Bearfield, Branislav Kveton
2025	J	`jnl`	Multimodal LLMs as Customized Reward Models for Text-to-Image Generation. CoRR Shijie Zhou, Ruiyi Zhang, Huaisheng Zhu, Branislav Kveton, Yufan Zhou, Jiuxiang Gu, Jian Chen, Changyou Chen
2025	A*	`conf`	OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models. ICLR 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	J	`jnl`	Personalization of Large Language Models: A Survey. Trans. Mach. Learn. Res. Zhehao Zhang, Ryan A. Rossi, Branislav Kveton, Yijia Shao, Diyi Yang, Hamed Zamani, Franck Dernoncourt, Joe Barrow, Tong Yu, Sungchul Kim, Ruiyi Zhang, Jiuxiang Gu, Tyler Derr, Hongjie Chen, Junda Wu, Xiang Chen, Zichao Wang, Subrata Mitra, Nedim Lipka, Nesreen K. Ahmed, Yu Wang
2025	J	`jnl`	Quantitative LLM Judges. CoRR Aishwarya Sahoo, Jeevana Kruthi Karnuthala, Tushar Parmanand Budhwani, Pranchal Agarwal, Sankaran Vaidyanathan, Alexa F. Siu, Franck Dernoncourt, Jennifer Healey, Nedim Lipka, Ryan A. Rossi, Uttaran Bhattacharya, Branislav Kveton
2025	J	`jnl`	RADAR: Reasoning-Ability and Difficulty-Aware Routing for Reasoning LLMs. CoRR Nigel Fernandez, Branislav Kveton, Ryan A. Rossi, Andrew S. Lan, Jack Zichao Wang
2025	A*	`conf`	RecGaze: The First Eye Tracking and User Interaction Dataset for Carousel Interfaces. SIGIR Santiago de Leon-Martinez, Jingwei Kang, Róbert Móro, Maarten de Rijke, Branislav Kveton, Harrie Oosterhuis, Mária Bieliková
2025	J	`jnl`	RecGaze: The First Eye Tracking and User Interaction Dataset for Carousel Interfaces. CoRR Santiago de Leon-Martinez, Jingwei Kang, Róbert Móro, Maarten de Rijke, Branislav Kveton, Harrie Oosterhuis, Mária Bieliková
2025	J	`jnl`	Riding the Carousel: The First Extensive Eye Tracking Analysis of Browsing Behavior in Carousel Recommenders. CoRR Santiago de Leon-Martinez, Róbert Móro, Branislav Kveton, Mária Bieliková
2025	A*	`conf`	Selective Uncertainty Propagation in Offline RL. AAAI Sanath Kumar Krishnamurthy, Tanmay Gangwani, Sumeet Katariya, Branislav Kveton, Shrey Modi, Anshuka Rangi
2025	J	`jnl`	StreamGaze: Gaze-Guided Temporal Reasoning and Proactive Understanding in Streaming Videos. CoRR Daeun Lee, Subhojyoti Mukherjee, Branislav Kveton, Ryan A. Rossi, Viet Dac Lai, Seunghyun Yoon, Trung Bui, Franck Dernoncourt, Mohit Bansal
2025	J	`jnl`	Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models. CoRR Chengkai Huang, Junda Wu, Yu Xia, Zixu Yu, Ruhan Wang, Tong Yu, Ruiyi Zhang, Ryan A. Rossi, Branislav Kveton, Dongruo Zhou, Julian J. McAuley, Lina Yao
2024	J	`jnl`	Comparing Few to Rank Many: Active Human Preference Learning using Randomized Frank-Wolfe. CoRR Kiran Koshy Thekumparampil, Gaurush Hiranandani, Kousha Kalantari, Shoham Sabach, Branislav Kveton
2024	J	`jnl`	Cross-Validated Off-Policy Evaluation. CoRR Matej Cief, Branislav Kveton, Michal Kompan
2024	J	`jnl`	Experimental Design for Active Transductive Inference in Large Language Models. CoRR Subhojyoti Mukherjee, Ge Liu, Aniket Deshmukh, Anusha Lalitha, Yifei Ma, Branislav Kveton
2024	J	`jnl`	GUI Agents: A Survey. CoRR 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, Thien Huu Nguyen, Trung Bui, Tianyi Zhou, Ryan A. Rossi, Franck Dernoncourt
2024	J	`jnl`	Language-Model Prior Overcomes Cold-Start Items. CoRR Shiyu Wang, Hao Ding, Yupeng Gu, Sergül Aydöre, Kousha Kalantari, Branislav Kveton
2024	A	`conf`	Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs. WSDM Behnam Rahdari, Hao Ding, Ziwei Fan, Yifei Ma, Zhuotong Chen, Anoop Deoras, Branislav Kveton
2024	A*	`conf`	MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent. ICML Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher
2024	J	`jnl`	MADA: Meta-Adaptive Optimizers through hyper-gradient Descent. CoRR Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher
2024	J	`jnl`	Multi-Objective Alignment of Large Language Models Through Hypervolume Maximization. CoRR Subhojyoti Mukherjee, Anusha Lalitha, Sailik Sengupta, Aniket Deshmukh, Branislav Kveton
2024	J	`jnl`	OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models. CoRR 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
2024	J	`jnl`	Off-Policy Evaluation from Logged Human Feedback. CoRR Aniruddha Bhargava, Lalit Jain, Branislav Kveton, Ge Liu, Subhojyoti Mukherjee
2024	A*	`conf`	Online Posterior Sampling with a Diffusion Prior. NeurIPS Branislav Kveton, Boris Oreshkin, Youngsuk Park, Aniket Deshmukh, Rui Song
2024	J	`jnl`	Online Posterior Sampling with a Diffusion Prior. CoRR Branislav Kveton, Boris Oreshkin, Youngsuk Park, Aniket Deshmukh, Rui Song
2024	A*	`conf`	Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling. ICLR Aadirupa Saha, Branislav Kveton
2024	J	`jnl`	Optimal Design for Human Feedback. CoRR Subhojyoti Mukherjee, Anusha Lalitha, Kousha Kalantari, Aniket Deshmukh, Ge Liu, Yifei Ma, Branislav Kveton
2024	A*	`conf`	Optimal Design for Human Preference Elicitation. NeurIPS Subhojyoti Mukherjee, Anusha Lalitha, Kousha Kalantari, Aniket Deshmukh, Ge Liu, Yifei Ma, Branislav Kveton
2024	J	`jnl`	Personalization of Large Language Models: A Survey. CoRR Zhehao Zhang, Ryan A. Rossi, Branislav Kveton, Yijia Shao, Diyi Yang, Hamed Zamani, Franck Dernoncourt, Joe Barrow, Tong Yu, Sungchul Kim, Ruiyi Zhang, Jiuxiang Gu, Tyler Derr, Hongjie Chen, Junda Wu, Xiang Chen, Zichao Wang, Subrata Mitra, Nedim Lipka, Nesreen K. Ahmed, Yu Wang
2024	A	`conf`	Pessimistic Off-Policy Multi-Objective Optimization. AISTATS Shima Alizadeh, Aniruddha Bhargava, Karthick Gopalswamy, Lalit Jain, Branislav Kveton, Ge Liu
2024	A	`conf`	Pessimistic Off-Policy Optimization for Learning to Rank. ECAI Matej Cief, Branislav Kveton, Michal Kompan
2024	A	`conf`	Pre-trained Recommender Systems: A Causal Debiasing Perspective. WSDM Ziqian Lin, Hao Ding, Trong Nghia Hoang, Branislav Kveton, Anoop Deoras, Hao Wang
2024	J	`jnl`	Towards Simulation-Based Evaluation of Recommender Systems with Carousel Interfaces. Trans. Recomm. Syst. Behnam Rahdari, Peter Brusilovsky, Branislav Kveton
2023	J	`jnl`	Efficient and Interpretable Bandit Algorithms. CoRR Subhojyoti Mukherjee, Ruihao Zhu, Branislav Kveton
2023	A	`conf`	Fixed-Budget Best-Arm Identification with Heterogeneous Reward Variances. UAI Anusha Lalitha, Kousha Kalantari, Yifei Ma, Anoop Deoras, Branislav Kveton
2023	J	`jnl`	Fixed-Budget Best-Arm Identification with Heterogeneous Reward Variances. CoRR Anusha Lalitha, Kousha Kalantari, Yifei Ma, Anoop Deoras, Branislav Kveton
2023	A*	`conf`	Logarithmic Bayes Regret Bounds. NeurIPS Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi
2023	J	`jnl`	Logarithmic Bayes Regret Bounds. CoRR Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi
2023	J	`jnl`	Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs. CoRR Behnam Rahdari, Hao Ding, Ziwei Fan, Yifei Ma, Zhuotong Chen, Anoop Deoras, Branislav Kveton
2023	A*	`conf`	Meta-Learning for Simple Regret Minimization. AAAI Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh, Sumeet Katariya
2023	A	`conf`	Mixed-Effect Thompson Sampling. AISTATS Imad Aouali, Branislav Kveton, Sumeet Katariya
2023	A*	`conf`	Multi-Task Off-Policy Learning from Bandit Feedback. ICML Joey Hong, Branislav Kveton, Manzil Zaheer, Sumeet Katariya, Mohammad Ghavamzadeh
2023	A*	`conf`	Multiplier Bootstrap-based Exploration. ICML Runzhe Wan, Haoyu Wei, Branislav Kveton, Rui Song
2023	J	`jnl`	Multiplier Bootstrap-based Exploration. CoRR Runzhe Wan, Haoyu Wei, Branislav Kveton, Rui Song
2023	A	`conf`	Non-Compliant Bandits. CIKM Branislav Kveton, Yi Liu, Johan Matteo Kruijssen, Yisu Nie
2023	J	`jnl`	Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling. CoRR Aadirupa Saha, Branislav Kveton
2023	J	`jnl`	Pessimistic Off-Policy Multi-Objective Optimization. CoRR Shima Alizadeh, Aniruddha Bhargava, Karthick Gopalswamy, Lalit Jain, Branislav Kveton, Ge Liu
2023	J	`jnl`	Pre-trained Recommender Systems: A Causal Debiasing Perspective. CoRR Ziqian Lin, Hao Ding, Nghia Hoang, Branislav Kveton, Anoop Deoras, Hao Wang
2023	J	`jnl`	Selective Uncertainty Propagation in Offline RL. CoRR Sanath Kumar Krishnamurthy, Tanmay Gangwani, Sumeet Katariya, Branislav Kveton, Anshuka Rangi
2023	A*	`conf`	Thompson Sampling with Diffusion Generative Prior. ICML Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blöbaum
2023	J	`jnl`	Thompson Sampling with Diffusion Generative Prior. CoRR Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blöbaum
2023	—	`conf`	Towards Sequential Counterfactual Learning to Rank. SIGIR-AP Tesi Xiao, Branislav Kveton, Sumeet Katariya, Tanmay Gangwani, Anshuka Rangi
2023	A	`conf`	Trending Now: Modeling Trend Recommendations. RecSys Hao Ding, Branislav Kveton, Yifei Ma, Youngsuk Park, Venkataramana Kini, Yupeng Gu, Ravi Divvela, Fei Wang, Anoop Deoras, Hao Wang
2022	J	`jnl`	Bayesian Fixed-Budget Best-Arm Identification. CoRR Alexia Atsidakou, Sumeet Katariya, Sujay Sanghavi, Branislav Kveton
2022	A*	`conf`	Deep Hierarchy in Bandits. ICML Joey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh
2022	J	`jnl`	Deep Hierarchy in Bandits. CoRR Joey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh
2022	A*	`conf`	Fixed-Budget Best-Arm Identification in Structured Bandits. IJCAI Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh
2022	J	`jnl`	From Ranked Lists to Carousels: A Carousel Click Model. CoRR Behnam Rahdari, Branislav Kveton, Peter Brusilovsky
2022	J	`jnl`	Generalizing Hierarchical Bayesian Bandits. CoRR Imad Aouali, Branislav Kveton, Sumeet Katariya
2022	A	`conf`	Hierarchical Bayesian Bandits. AISTATS Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh
2022	J	`jnl`	IMO CoRR Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton, Craig Boutilier
2022	A*	`conf`	IMO^3: Interactive Multi-Objective Off-Policy Optimization. IJCAI Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton, Craig Boutilier
2022	J	`jnl`	Meta-Learning for Simple Regret Minimization. CoRR Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh, Sumeet Katariya
2022	J	`jnl`	Multi-Task Off-Policy Learning from Bandit Feedback. CoRR Joey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh
2022	A	`conf`	On the Value of Prior in Online Learning to Rank. AISTATS Branislav Kveton, Ofer Meshi, Masrour Zoghi, Zhen Qin
2022	J	`jnl`	Optimal probing with statistical guarantees for network monitoring at scale. Comput. Commun. Branislav Kveton, Muhammad Jehangir Amjad, Christophe Diot, Dimitris Konomis, Augustin Soule, Xiaolong Yang
2022	J	`jnl`	Pessimistic Off-Policy Optimization for Learning to Rank. CoRR Matej Cief, Branislav Kveton, Michal Kompan
2022	A	`conf`	Random Effect Bandits. AISTATS Rong Zhu, Branislav Kveton
2022	J	`jnl`	Robust Contextual Linear Bandits. CoRR Rong Zhu, Branislav Kveton
2022	A*	`conf`	Safe Exploration for Efficient Policy Evaluation and Comparison. ICML Runzhe Wan, Branislav Kveton, Rui Song
2022	J	`jnl`	Safe Exploration for Efficient Policy Evaluation and Comparison. CoRR Runzhe Wan, Branislav Kveton, Rui Song
2022	A	`conf`	Safe Optimal Design with Applications in Off-Policy Learning. AISTATS Ruihao Zhu, Branislav Kveton
2022	—	`conf`	The Magic of Carousels: Single vs. Multi-List Recommender Systems. HT Behnam Rahdari, Branislav Kveton, Peter Brusilovsky
2022	A	`conf`	Thompson Sampling with a Mixture Prior. AISTATS Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier
2022	Misc	`conf`	Towards Increasing the Coverage of Interactive Recommendations. FLAIRS Behnam Rahdari, Peter Brusilovsky, Branislav Kveton
2022	A*	`conf`	Uplifting Bandits. NeurIPS Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton
2022	J	`jnl`	Uplifting Bandits. CoRR Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton
2021	A	`conf`	CORe: Capitalizing On Rewards in Bandit Exploration. UAI Nan Wang, Branislav Kveton, Maryam Karimzadehgan
2021	J	`jnl`	CORe: Capitalizing On Rewards in Bandit Exploration. CoRR Nan Wang, Branislav Kveton, Maryam Karimzadehgan
2021	J	`jnl`	Fixed-Budget Best-Arm Identification in Contextual Bandits: A Static-Adaptive Algorithm. CoRR Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh
2021	J	`jnl`	Hierarchical Bayesian Bandits. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh
2021	A*	`conf`	Meta-Thompson Sampling. ICML Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvári
2021	J	`jnl`	Meta-Thompson Sampling. CoRR Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvári
2021	A*	`conf`	No Regrets for Learning the Prior in Bandits. NeurIPS Soumya Basu, Branislav Kveton, Manzil Zaheer, Csaba Szepesvári
2021	J	`jnl`	No Regrets for Learning the Prior in Bandits. CoRR Soumya Basu, Branislav Kveton, Manzil Zaheer, Csaba Szepesvári
2021	A	`conf`	Non-Stationary Off-Policy Optimization. AISTATS Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed
2021	J	`jnl`	Optimal Probing with Statistical Guarantees for Network Monitoring at Scale. CoRR Muhammad Jehangir Amjad, Christophe Diot, Dimitris Konomis, Branislav Kveton, Augustin Soule, Xiaolong Yang
2021	J	`jnl`	Random Effect Bandits. CoRR Rong Zhu, Branislav Kveton
2021	J	`jnl`	Safe Optimal Design with Applications in Policy Learning. CoRR Ruihao Zhu, Branislav Kveton
2021	J	`jnl`	Thompson Sampling with a Mixture Prior. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier
2020	J	`jnl`	Differentiable Bandit Exploration. CoRR Craig Boutilier, Chih-Wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvári, Manzil Zaheer
2020	J	`jnl`	Differentiable Meta-Learning in Contextual Bandits. CoRR Branislav Kveton, Martin Mladenov, Chih-Wei Hsu, Manzil Zaheer, Csaba Szepesvári, Craig Boutilier
2020	A*	`conf`	Differentiable Meta-Learning of Bandit Policies. NeurIPS Craig Boutilier, Chih-Wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvári, Manzil Zaheer
2020	A*	`conf`	Graphical Models Meet Bandits: A Variational Thompson Sampling Approach. ICML Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel
2020	J	`jnl`	Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems. CoRR Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel
2020	A*	`conf`	Latent Bandits Revisited. NeurIPS Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier
2020	J	`jnl`	Latent Bandits Revisited. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier
2020	J	`jnl`	Non-Stationary Latent Bandits. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Mohammad Ghavamzadeh, Craig Boutilier
2020	A	`conf`	Old Dog Learns New Tricks: Randomized UCB for Bandit Problems. AISTATS Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton
2020	J	`jnl`	Piecewise-Stationary Off-Policy Optimization. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed
2020	A	`conf`	Randomized Exploration in Generalized Linear Bandits. AISTATS Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier
2020	J	`jnl`	Sample Efficient Graph-Based Optimization with Noisy Observations. CoRR Thanh Tan Nguyen, Ali Shameli, Yasin Abbasi-Yadkori, Anup Rao, Branislav Kveton
2019	A	`conf`	BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback. UAI Chang Li, Branislav Kveton, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvári, Masrour Zoghi
2019	A	`conf`	Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank. UAI Gaurush Hiranandani, Harvineet Singh, Prakhar Gupta, Iftikhar Ahamath Burhanuddin, Zheng Wen, Branislav Kveton
2019	A	`conf`	Conservative Exploration using Interleaving. AISTATS Sumeet Katariya, Branislav Kveton, Zheng Wen, Vamsi K. Potluru
2019	J	`jnl`	Empirical Bayes Regret Minimization. CoRR Chih-Wei Hsu, Branislav Kveton, Ofer Meshi, Martin Mladenov, Csaba Szepesvári
2019	A*	`conf`	Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits. ICML Branislav Kveton, Csaba Szepesvári, Sharan Vaswani, Zheng Wen, Tor Lattimore, Mohammad Ghavamzadeh
2019	A	`conf`	Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit. AISTATS Yang Cao, Zheng Wen, Branislav Kveton, Yao Xie
2019	J	`jnl`	Old Dog Learns New Tricks: Randomized UCB for Bandit Problems. CoRR Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton
2019	A	`conf`	Perturbed-History Exploration in Stochastic Linear Bandits. UAI Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
2019	J	`jnl`	Perturbed-History Exploration in Stochastic Linear Bandits. CoRR Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
2019	A*	`conf`	Perturbed-History Exploration in Stochastic Multi-Armed Bandits. IJCAI Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
2019	J	`jnl`	Perturbed-History Exploration in Stochastic Multi-Armed Bandits. CoRR Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
2019	J	`jnl`	Randomized Exploration in Generalized Linear Bandits. CoRR Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier
2019	A	`conf`	Sample Efficient Graph-Based Optimization with Noisy Observations. AISTATS Thanh Tan Nguyen, Ali Shameli, Yasin Abbasi-Yadkori, Anup Rao, Branislav Kveton
2019	J	`jnl`	Waterfall Bandits: Learning to Sell Ads Online. CoRR Branislav Kveton, Saied Mahdian, S. Muthukrishnan, Zheng Wen, Yikun Xian
2018	J	`jnl`	BubbleRank: Safe Online Learning to Rerank. CoRR Branislav Kveton, Chang Li, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvári, Masrour Zoghi
2018	J	`jnl`	Conservative Exploration using Interleaving. CoRR Sumeet Katariya, Branislav Kveton, Zheng Wen, Vamsi K. Potluru
2018	A	`conf`	Efficient online recommendation via low-rank ensemble sampling. RecSys Xiuyuan Lu, Zheng Wen, Branislav Kveton
2018	A*	`conf`	Finding Subcube Heavy Hitters in Analytics Data Streams. WWW Branislav Kveton, S. Muthukrishnan, Hoa T. Vu, Yikun Xian
2018	J	`jnl`	Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits. CoRR Branislav Kveton, Csaba Szepesvári, Zheng Wen, Mohammad Ghavamzadeh, Tor Lattimore
2018	J	`jnl`	Nearly Optimal Adaptive Procedure for Piecewise-Stationary Bandit: a Change-Point Detection Approach. CoRR Yang Cao, Zheng Wen, Branislav Kveton, Yao Xie
2018	J	`jnl`	New Insights into Bootstrapping for Bandits. CoRR Sharan Vaswani, Branislav Kveton, Zheng Wen, Anup Rao, Mark Schmidt, Yasin Abbasi-Yadkori
2018	A*	`conf`	Offline Evaluation of Ranking Policies with Click Models. KDD Shuai Li, Yasin Abbasi-Yadkori, Branislav Kveton, S. Muthukrishnan, Vishwa Vinay, Zheng Wen
2018	J	`jnl`	Offline Evaluation of Ranking Policies with Click Models. CoRR Shuai Li, Yasin Abbasi-Yadkori, Branislav Kveton, S. Muthukrishnan, Vishwa Vinay, Zheng Wen
2018	J	`jnl`	Online Diverse Learning to Rank from Partial-Click Feedback. CoRR Prakhar Gupta, Gaurush Hiranandani, Harvineet Singh, Branislav Kveton, Zheng Wen, Iftikhar Ahamath Burhanuddin
2018	A	`conf`	Predictive Analysis by Leveraging Temporal User Behavior and User Embeddings. CIKM Charles Chen, Sungchul Kim, Hung Bui, Ryan A. Rossi, Eunyee Koh, Branislav Kveton, Razvan C. Bunescu
2018	—	`conf`	SpectralLeader: Online Spectral Learning for Single Topic Models. ECML/PKDD (2) Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel
2018	A*	`conf`	TopRank: A practical algorithm for online stochastic ranking. NeurIPS Tor Lattimore, Branislav Kveton, Shuai Li, Csaba Szepesvári
2018	J	`jnl`	TopRank: A practical algorithm for online stochastic ranking. CoRR Tor Lattimore, Branislav Kveton, Shuai Li, Csaba Szepesvári
2017	A*	`conf`	Bernoulli Rank-1 Bandits for Click Feedback. IJCAI Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Claire Vernade, Zheng Wen
2017	J	`jnl`	Bernoulli Rank-1 Bandits for Click Feedback. CoRR Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Claire Vernade, Zheng Wen
2017	J	`jnl`	Diffusion Independent Semi-Bandit Influence Maximization. CoRR Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt
2017	J	`jnl`	Does Weather Matter? Causal Analysis of TV Logs. CoRR Shi Zong, Branislav Kveton, Shlomo Berkovsky, Azin Ashkan, Nikos Vlassis, Zheng Wen
2017	—	`conf`	Does Weather Matter?: Causal Analysis of TV Logs. WWW (Companion Volume) Shi Zong, Branislav Kveton, Shlomo Berkovsky, Azin Ashkan, Nikos Vlassis, Zheng Wen
2017	J	`jnl`	Finding Subcube Heavy Hitters in Data Streams. CoRR Branislav Kveton, S. Muthukrishnan, Hoa T. Vu
2017	A	`conf`	Get to the Bottom: Causal Analysis for User Modeling. UMAP Shi Zong, Branislav Kveton, Shlomo Berkovsky, Azin Ashkan, Zheng Wen
2017	A*	`conf`	Model-Independent Online Learning for Influence Maximization. ICML Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt
2017	—	`conf`	Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback. NIPS Zheng Wen, Branislav Kveton, Michal Valko, Sharan Vaswani
2017	A*	`conf`	Online Learning to Rank in Stochastic Click Models. ICML Masrour Zoghi, Tomás Tunys, Mohammad Ghavamzadeh, Branislav Kveton, Csaba Szepesvári, Zheng Wen
2017	J	`jnl`	Online Learning to Rank in Stochastic Click Models. CoRR Mohammad Ghavamzadeh, Branislav Kveton, Csaba Szepesvári, Tomás Tunys, Zheng Wen, Masrour Zoghi
2017	J	`jnl`	SpectralFPL: Online Spectral Learning for Single Topic Models. CoRR Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel
2017	J	`jnl`	Stochastic Low-Rank Bandits. CoRR Branislav Kveton, Csaba Szepesvári, Anup Rao, Zheng Wen, Yasin Abbasi-Yadkori, S. Muthukrishnan
2017	A	`conf`	Stochastic Rank-1 Bandits. AISTATS Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Claire Vernade, Zheng Wen
2017	—	`conf`	Thompson Sampling for Optimizing Stochastic Local Search. ECML/PKDD (1) Tong Yu, Branislav Kveton, Ole J. Mengshoel
2016	A	`conf`	Cascading Bandits for Large-Scale Recommendation Problems. UAI Shi Zong, Hao Ni, Kenny Sung, Nan Rosemary Ke, Zheng Wen, Branislav Kveton
2016	J	`jnl`	Cascading Bandits for Large-Scale Recommendation Problems. CoRR Shi Zong, Hao Ni, Kenny Sung, Nan Rosemary Ke, Zheng Wen, Branislav Kveton
2016	A*	`conf`	DCM Bandits: Learning to Rank with Multiple Clicks. ICML Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Zheng Wen
2016	J	`jnl`	DCM Bandits: Learning to Rank with Multiple Clicks. CoRR Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Zheng Wen
2016	—	`conf`	Graphical Model Sketch. ECML/PKDD (1) Branislav Kveton, Hung Bui, Mohammad Ghavamzadeh, Georgios Theocharous, S. Muthukrishnan, Siqi Sun
2016	J	`jnl`	Graphical Model Sketch. CoRR Branislav Kveton, Hung Bui, Mohammad Ghavamzadeh, Georgios Theocharous, S. Muthukrishnan, Siqi Sun
2016	J	`jnl`	Influence Maximization with Semi-Bandit Feedback. CoRR Zheng Wen, Branislav Kveton, Michal Valko
2016	J	`jnl`	Minimal Interaction Content Discovery in Recommender Systems. ACM Trans. Interact. Intell. Syst. Branislav Kveton, Shlomo Berkovsky
2016	A*	`conf`	Practical Linear Models for Large-Scale One-Class Collaborative Filtering. IJCAI Suvash Sedhain, Hung Bui, Jaya Kawale, Nikos Vlassis, Branislav Kveton, Aditya Krishna Menon, Trung Bui, Scott Sanner
2016	J	`jnl`	Stochastic Rank-1 Bandits. CoRR Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Claire Vernade, Zheng Wen
2015	J	`jnl`	Cascading Bandits. CoRR Branislav Kveton, Csaba Szepesvári, Zheng Wen, Azin Ashkan
2015	A*	`conf`	Cascading Bandits: Learning to Rank in the Cascade Model. ICML Branislav Kveton, Csaba Szepesvári, Zheng Wen, Azin Ashkan
2015	—	`conf`	Combinatorial Cascading Bandits. NIPS Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvári
2015	J	`jnl`	Combinatorial Cascading Bandits. CoRR Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvári
2015	A*	`conf`	Efficient Learning in Large-Scale Combinatorial Semi-Bandits. ICML Zheng Wen, Branislav Kveton, Azin Ashkan
2015	—	`conf`	Efficient Thompson Sampling for Online Matrix-Factorization Recommendation. NIPS Jaya Kawale, Hung Hai Bui, Branislav Kveton, Long Tran-Thanh, Sanjay Chawla
2015	J	`jnl`	Managing Your Private and Public Data: Bringing Down Inference Attacks Against Your Privacy. IEEE J. Sel. Top. Signal Process. Salman Salamatian, Amy Zhang, Flávio du Pin Calmon, Sandilya Bhamidipati, Nadia Fawaz, Branislav Kveton, Pedro Oliveira, Nina Taft
2015	A	`conf`	Minimal Interaction Search in Recommender Systems. IUI Branislav Kveton, Shlomo Berkovsky
2015	A*	`conf`	Optimal Greedy Diversity for Recommendation. IJCAI Azin Ashkan, Branislav Kveton, Shlomo Berkovsky, Zheng Wen
2015	J	`jnl`	PriView: Personalized Media Consumption Meets Privacy against Inference Attacks. IEEE Softw. Sandilya Bhamidipati, Nadia Fawaz, Branislav Kveton, Amy Zhang
2015	A	`conf`	Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits. AISTATS Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvári
2014	J	`jnl`	DUM: Diversity-Weighted Utility Maximization for Recommendations. CoRR Azin Ashkan, Branislav Kveton, Shlomo Berkovsky, Zheng Wen
2014	—	`conf`	Diversified Utility Maximization for Recommendations. RecSys Posters Azin Ashkan, Branislav Kveton, Shlomo Berkovsky, Zheng Wen
2014	J	`jnl`	Efficient Learning in Large-Scale Combinatorial Semi-Bandits. CoRR Zheng Wen, Azin Ashkan, Hoda Eydgahi, Branislav Kveton
2014	A*	`conf`	Large-Scale Optimistic Adaptive Submodularity. AAAI Victor Gabillon, Branislav Kveton, Zheng Wen, Brian Eriksson, S. Muthukrishnan
2014	J	`jnl`	Learning to Act Greedily: Polymatroid Semi-Bandits. CoRR Branislav Kveton, Zheng Wen, Azin Ashkan, Michal Valko
2014	J	`jnl`	Managing your Private and Public Data: Bringing down Inference Attacks against your Privacy. CoRR Salman Salamatian, Amy Zhang, Flávio du Pin Calmon, Sandilya Bhamidipati, Nadia Fawaz, Branislav Kveton, Pedro Oliveira, Nina Taft
2014	A	`conf`	Matroid Bandits: Fast Combinatorial Optimization with Learning. UAI Branislav Kveton, Zheng Wen, Azin Ashkan, Hoda Eydgahi, Brian Eriksson
2014	J	`jnl`	Matroid Bandits: Fast Combinatorial Optimization with Learning. CoRR Branislav Kveton, Zheng Wen, Azin Ashkan, Hoda Eydgahi, Brian Eriksson
2014	A	`conf`	SPPM: Sparse Privacy Preserving Mappings. UAI Salman Salamatian, Nadia Fawaz, Branislav Kveton, Nina Taft
2014	A*	`conf`	Spectral Bandits for Smooth Graph Functions. ICML Michal Valko, Rémi Munos, Branislav Kveton, Tomás Kocák
2014	J	`jnl`	Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits. CoRR Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvári
2013	—	`conf`	Adaptive Submodular Maximization in Bandit Setting. NIPS Victor Gabillon, Branislav Kveton, Zheng Wen, Brian Eriksson, S. Muthukrishnan
2013	—	`conf`	How to hide the elephant- or the donkey- in the room: Practical privacy against statistical inference for large data. GlobalSIP Salman Salamatian, Amy Zhang, Flávio du Pin Calmon, Sandilya Bhamidipati, Nadia Fawaz, Branislav Kveton, Pedro Oliveira, Nina Taft
2013	B	`conf`	Learning from a single labeled face and a stream of unlabeled data. FG Branislav Kveton, Michal Valko
2013	A*	`conf`	Predicting user dissatisfaction with Internet application performance at end-hosts. INFOCOM Diana Joumblatt, Jaideep Chandrashekar, Branislav Kveton, Nina Taft, Renata Teixeira
2013	—	`conf`	Sequential Bayesian Search. ICML (2) Zheng Wen, Branislav Kveton, Brian Eriksson, Sandilya Bhamidipati
2013	A*	`conf`	Structured Kernel-Based Reinforcement Learning. AAAI Branislav Kveton, Georgios Theocharous
2012	J	`jnl`	Automatic Tuning of Interactive Perception Applications CoRR Qian Zhu, Branislav Kveton, Lily B. Mummert, Padmanabhan Pillai
2012	—	`conf`	Incorporating Metadata into Dynamic Topic Analysis. BMA Tianxi Li, Branislav Kveton, Yu Wu, Ashwin Kashyap
2012	A*	`conf`	Kernel-Based Reinforcement Learning on Representative States. AAAI Branislav Kveton, Georgios Theocharous
2012	J	`jnl`	Leveraging Side Observations in Stochastic Bandits CoRR Stéphane Caron, Branislav Kveton, Marc Lelarge, Smriti Bhagat
2012	A	`conf`	Leveraging Side Observations in Stochastic Bandits. UAI Stéphane Caron, Branislav Kveton, Marc Lelarge, Smriti Bhagat
2012	J	`jnl`	Online Semi-Supervised Learning on Quantized Graphs CoRR Michal Valko, Branislav Kveton, Ling Huang, Daniel Ting
2012	J	`jnl`	Partitioned Linear Programming Approximations for MDPs CoRR Branislav Kveton, Milos Hauskrecht
2012	J	`jnl`	Solving Factored MDPs with Continuous and Discrete Variables CoRR Carlos Guestrin, Milos Hauskrecht, Branislav Kveton
2011	—	`conf`	Automatic Identity Inference for Smart TVs. Lifelong Learning Avneesh Singh Saluja, Frank Mokaya, Mariano Phielipp, Branislav Kveton
2011	A*	`conf`	Conditional Anomaly Detection with Soft Harmonic Functions. ICDM Michal Valko, Branislav Kveton, Hamed Valizadegan, Gregory F. Cooper, Milos Hauskrecht
2011	J	`jnl`	Solving Factored MDPs with Hybrid State and Action Variables CoRR Carlos Guestrin, Milos Hauskrecht, Branislav Kveton
2010	A	`conf`	Automatic Tuning of Interactive Perception Applications. UAI Qian Zhu, Branislav Kveton, Lily B. Mummert, Padmanabhan Pillai
2010	C	`conf`	Fast, Accurate, and Practical Identity Inference Using TV Remote Controls. IAAI Mariano Phielipp, Magdiel Galan, Richard Lee, Branislav Kveton, Jeffrey Hightower
2010	A	`conf`	Online Semi-Supervised Learning on Quantized Graphs. UAI Michal Valko, Branislav Kveton, Ling Huang, Daniel Ting
2010	—	`conf`	Online semi-supervised perception: Real-time learning without explicit feedback. CVPR Workshops Branislav Kveton, Matthai Philipose, Michal Valko, Ling Huang
2010	A	`conf`	Semi-Supervised Learning with Max-Margin Graph Cuts. AISTATS Branislav Kveton, Michal Valko, Ali Rahimi, Ling Huang
2009	—	`conf`	Inferring Identity Using Accelerometers in Television Remote Controls. Pervasive Keng-hao Chang, Jeffrey Hightower, Branislav Kveton
2008	Misc	`conf`	A Lazy Approach to Online Learning with Constraints. ISAIM Branislav Kveton, Jia Yuan Yu, Georgios Theocharous, Shie Mannor
2008	A*	`conf`	Online Learning with Expert Advice and Finite-Horizon Constraints. AAAI Branislav Kveton, Jia Yuan Yu, Georgios Theocharous, Shie Mannor
2008	A	`conf`	Partitioned Linear Programming Approximations for MDPs. UAI Branislav Kveton, Milos Hauskrecht
2007	A*	`conf`	Adaptive Timeout Policies for Fast Fine-Grained Power Management. AAAI Branislav Kveton, Prashant Gandhi, Georgios Theocharous, Shie Mannor, Barbara Rosario, Nilesh Shah
2007	Misc	`conf`	Evidence-based Anomaly Detection in Clinical Domains. AMIA Milos Hauskrecht, Michal Valko, Branislav Kveton, Shyam Visweswaran, Gregory F. Cooper
2006	A*	`conf`	Learning Basis Functions in Hybrid Domains. AAAI Branislav Kveton, Milos Hauskrecht
2006	A*	`conf`	Solving Factored MDPs with Exponential-Family Transition Models. ICAPS Branislav Kveton, Milos Hauskrecht
2006	J	`jnl`	Solving Factored MDPs with Hybrid State and Action Variables. J. Artif. Intell. Res. Branislav Kveton, Milos Hauskrecht, Carlos Guestrin
2006	A*	`conf`	When Gossip is Good: Distributed Probabilistic Inference for Detection of Slow Network Intrusions. AAAI Denver Dash, Branislav Kveton, John Mark Agosta, Eve M. Schooler, Jaideep Chandrashekar, Abraham Bachrach, Alex Newman
2005	A*	`conf`	An MCMC Approach to Solving Hybrid Factored MDPs. IJCAI Branislav Kveton, Milos Hauskrecht
2005	Misc	`conf`	Automatic Excursion Detection in Manufacturing: Preliminary Results. FLAIRS Branislav Kveton, Denver Dash
2004	A*	`conf`	Heuristic Refinements of Approximate Linear Programming for Factored Continuous-State Markov Decision Processes. ICAPS Branislav Kveton, Milos Hauskrecht
2004	A	`conf`	Solving Factored MDPs with Continuous and Discrete Variables. UAI Carlos Guestrin, Milos Hauskrecht, Branislav Kveton
2003	—	`conf`	Linear Program Approximations for Factored Continuous-State Markov Decision Processes. NIPS Milos Hauskrecht, Branislav Kveton