Sattar Vakili - RankMe

81 papers A* 17A 5B 5Misc 6Journal 43Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	MixFlow: Mixture-Conditioned Flow Matching for Out-of-Distribution Generalization. CoRR Andrea Rubbi, Amir Akbarnejad, Mohammad V. Sanian, Aryan Yazdan Parast, Hesam Asadollahzadeh, Arian Amani, Naveed Akhtar, Sarah Cooper, Andrew Bassett, Pietro Liò, Lassi Paavolainen, Sattar Vakili, Mohammad Lotfollahi
2025	A*	`conf`	Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds. ICML Aya Kayal, Sattar Vakili, Laura Toni, Da-Shan Shiu, Alberto Bernacchia
2025	J	`jnl`	Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds. CoRR Aya Kayal, Sattar Vakili, Laura Toni, Da-Shan Shiu, Alberto Bernacchia
2025	J	`jnl`	Group Think: Multiple Concurrent Reasoning Agents Collaborating at Token Level Granularity. CoRR Chan-Jan Hsu, Davide Buffelli, Jamie McGowan, Feng-Ting Liao, Yi-Chang Chen, Sattar Vakili, Da-Shan Shiu
2025	J	`jnl`	Near-Optimal Sample Complexity in Reward-Free Kernel-Based Reinforcement Learning. CoRR Aya Kayal, Sattar Vakili, Laura Toni, Alberto Bernacchia
2025	A	`conf`	Near-Optimal Sample Complexity in Reward-Free Kernel-based Reinforcement Learning. AISTATS Aya Kayal, Sattar Vakili, Laura Toni, Alberto Bernacchia
2025	J	`jnl`	No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes. CoRR Jasmine Bayrooti, Sattar Vakili, Amanda Prorok, Carl Henrik Ek
2025	J	`jnl`	Reinforcement Learning Using known Invariances. CoRR Alexandru Cioba, Aya Kayal, Laura Toni, Sattar Vakili, Alberto Bernacchia
2025	J	`jnl`	Towards a Foundation Model for Communication Systems. CoRR Davide Buffelli, Sowmen Das, Yu-Wei Lin, Sattar Vakili, Chien-Yi Wang, Masoud Attarifar, Pritthijit Nath, Da-Shan Shiu
2024	B	`conf`	Adversarial Contextual Bandits Go Kernelized. ALT Gergely Neu, Julia Olkhovskaya, Sattar Vakili
2024	A*	`conf`	Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm. NeurIPS Sattar Vakili, Julia Olkhovskaya
2024	J	`jnl`	Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm. CoRR Sattar Vakili, Julia Olkhovskaya
2024	A*	`conf`	Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning. COLT Sattar Vakili
2024	J	`jnl`	Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning. CoRR Sattar Vakili
2024	B	`conf`	Optimal Regret Bounds for Collaborative Learning in Bandits. ALT Amitis Shidani, Sattar Vakili
2024	A*	`conf`	Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency. ICML Sudeep Salgia, Sattar Vakili, Qing Zhao
2024	A*	`conf`	Reward-Free Kernel-Based Reinforcement Learning. ICML Sattar Vakili, Farhang Nabiei, Da-Shan Shiu, Alberto Bernacchia
2023	J	`jnl`	Adversarial Contextual Bandits Go Kernelized. CoRR Gergely Neu, Julia Olkhovskaya, Sattar Vakili
2023	J	`jnl`	Collaborative Learning in Kernel-Based Bandits for Distributed Users. IEEE Trans. Signal Process. Sudeep Salgia, Sattar Vakili, Qing Zhao
2023	A*	`conf`	Delayed Feedback in Kernel Bandits. ICML Sattar Vakili, Danyal Ahmed, Alberto Bernacchia, Ciara Pike-Burke
2023	J	`jnl`	Delayed Feedback in Kernel Bandits. CoRR Sattar Vakili, Danyal Ahmed, Alberto Bernacchia, Ciara Pike-Burke
2023	A*	`conf`	Fisher-Legendre (FishLeg) optimization of deep neural networks. ICLR Jezabel R. Garcia, Federica Freddi, Stathi Fotiadis, Maolin Li, Sattar Vakili, Alberto Bernacchia, Guillaume Hennequin
2023	B	`conf`	Generative Diffusion Models for Radio Wireless Channel Modelling and Sampling. GLOBECOM Ushnish Sengupta, Chinkuo Jao, Alberto Bernacchia, Sattar Vakili, Da-Shan Shiu
2023	J	`jnl`	Generative Diffusion Models for Radio Wireless Channel Modelling and Sampling. CoRR Ushnish Sengupta, Chinkuo Jao, Alberto Bernacchia, Sattar Vakili, Da-Shan Shiu
2023	A*	`conf`	Image generation with shortest path diffusion. ICML Ayan Das, Stathi Fotiadis, Anil Batra, Farhang Nabiei, Fengting Liao, Sattar Vakili, Da-Shan Shiu, Alberto Bernacchia
2023	J	`jnl`	Image generation with shortest path diffusion. CoRR Ayan Das, Stathi Fotiadis, Anil Batra, Farhang Nabiei, Feng-Ting Liao, Sattar Vakili, Da-Shan Shiu, Alberto Bernacchia
2023	B	`conf`	Information Gain and Uniform Generalization Bounds for Neural Kernel Models. ISIT Sattar Vakili, Michael Bromberg, Jezabel R. Garcia, Da-Shan Shiu, Alberto Bernacchia
2023	A*	`conf`	Kernelized Reinforcement Learning with Order Optimal Regret Bounds. NeurIPS Sattar Vakili, Julia Olkhovskaya
2023	J	`jnl`	Kernelized Reinforcement Learning with Order Optimal Regret Bounds. CoRR Sattar Vakili, Julia Olkhovskaya
2023	J	`jnl`	Optimal Regret Bounds for Collaborative Learning in Bandits. CoRR Amitis Shidani, Sattar Vakili
2023	J	`jnl`	Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency. CoRR Sudeep Salgia, Sattar Vakili, Qing Zhao
2023	J	`jnl`	Robust Best-arm Identification in Linear Bandits. CoRR Wei Wang, Sattar Vakili, Ilija Bogunovic
2023	A	`conf`	Sample Complexity of Kernel-Based Q-Learning. AISTATS Sing-Yuan Yeh, Fu-Chieh Chang, Chang-Wei Yueh, Pei-Yuan Wu, Alberto Bernacchia, Sattar Vakili
2023	J	`jnl`	Sample Complexity of Kernel-Based Q-Learning. CoRR Sing-Yuan Yeh, Fu-Chieh Chang, Chang-Wei Yueh, Pei-Yuan Wu, Alberto Bernacchia, Sattar Vakili
2023	J	`jnl`	Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow. CoRR Victor Picheny, Joel Berkeley, Henry B. Moss, Hrvoje Stojic, Uri Granta, Sebastian W. Ober, Artem Artemev, Khurram Ghani, Alexander Goodall, Andrei Paleyes, Sattar Vakili, Sergio Pascual-Diaz, Stratis Markou, Jixiang Qing, Nasrulloh R. B. S. Loka, Ivo Couckuyt
2022	A*	`conf`	Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning. ICML Sattar Vakili, Jonathan Scarlett, Da-Shan Shiu, Alberto Bernacchia
2022	J	`jnl`	Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning. CoRR Sattar Vakili, Jonathan Scarlett, Da-Shan Shiu, Alberto Bernacchia
2022	J	`jnl`	Kernel-based Federated Learning with Personalization. CoRR Sudeep Salgia, Sattar Vakili, Qing Zhao
2022	A*	`conf`	Near-Optimal Collaborative Learning in Bandits. NeurIPS Clémence Réda, Sattar Vakili, Emilie Kaufmann
2022	J	`jnl`	Near-Optimal Collaborative Learning in Bandits. CoRR Clémence Réda, Sattar Vakili, Emilie Kaufmann
2022	J	`jnl`	Provably and Practically Efficient Neural Contextual Bandits. CoRR Sudeep Salgia, Sattar Vakili, Qing Zhao
2021	A*	`conf`	A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance. NeurIPS Sudeep Salgia, Sattar Vakili, Qing Zhao
2021	A	`conf`	Gambler Bandits and the Regret of Being Ruined. AAMAS Filipo Studzinski Perotto, Sattar Vakili, Pratik Gajane, Yaser Faghan, Mathieu Bourgais
2021	A	`conf`	On Information Gain and Regret Bounds in Gaussian Process Bandits. AISTATS Sattar Vakili, Kia Khezeli, Victor Picheny
2021	A*	`conf`	Open Problem: Tight Online Confidence Intervals for RKHS Elements. COLT Sattar Vakili, Jonathan Scarlett, Tara Javidi
2021	J	`jnl`	Open Problem: Tight Online Confidence Intervals for RKHS Elements. CoRR Sattar Vakili, Jonathan Scarlett, Tara Javidi
2021	A*	`conf`	Optimal Order Simple Regret for Gaussian Process Bandits. NeurIPS Sattar Vakili, Nacime Bouziani, Sepehr Jalali, Alberto Bernacchia, Da-Shan Shiu
2021	J	`jnl`	Optimal Order Simple Regret for Gaussian Process Bandits. CoRR Sattar Vakili, Nacime Bouziani, Sepehr Jalali, Alberto Bernacchia, Da-Shan Shiu
2021	A*	`conf`	Scalable Thompson Sampling using Sparse Gaussian Process Models. NeurIPS Sattar Vakili, Henry B. Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny
2021	J	`jnl`	Uniform Generalization Bounds for Overparameterized Neural Networks. CoRR Sattar Vakili, Michael Bromberg, Da-Shan Shiu, Alberto Bernacchia
2020	J	`jnl`	A Computationally Efficient Approach to Black-box Optimization using Gaussian Process Models. CoRR Sudeep Salgia, Sattar Vakili, Qing Zhao
2020	A	`conf`	Amortized variance reduction for doubly stochastic objective. UAI Ayman Boustati, Sattar Vakili, James Hensman, S. T. John
2020	J	`jnl`	Amortized variance reduction for doubly stochastic objectives. CoRR Ayman Boustati, Sattar Vakili, James Hensman, S. T. John
2020	J	`jnl`	Multi-Armed Bandits on Partially Revealed Unit Interval Graphs. IEEE Trans. Netw. Sci. Eng. Xiao Xu, Sattar Vakili, Qing Zhao, Ananthram Swami
2020	J	`jnl`	On Information Gain and Regret Bounds in Gaussian Process Bandits. CoRR Sattar Vakili, Kia Khezeli, Victor Picheny
2020	J	`jnl`	Regret Bounds for Noise-Free Bayesian Optimization. CoRR Sattar Vakili, Victor Picheny, Nicolas Durrande
2020	J	`jnl`	Scalable Thompson Sampling using Sparse Gaussian Process Models. CoRR Sattar Vakili, Henry B. Moss, Victor Picheny, Vincent Dutordoir, Artem Artemev
2020	A*	`conf`	Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization. ICML Sudeep Salgia, Qing Zhao, Sattar Vakili
2020	J	`jnl`	Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization. CoRR Sudeep Salgia, Qing Zhao, Sattar Vakili
2019	B	`conf`	A Random Walk Approach to First-Order Stochastic Convex Optimization. ISIT Sattar Vakili, Qing Zhao
2019	J	`jnl`	A Random Walk Approach to First-Order Stochastic Convex Optimization. CoRR Sattar Vakili, Qing Zhao
2019	A*	`conf`	Adaptive Sensor Placement for Continuous Spaces. ICML James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote
2019	J	`jnl`	Adaptive Sensor Placement for Continuous Spaces. CoRR James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote
2019	—	`conf`	Decision Variance in Risk-Averse Online Learning. CDC Sattar Vakili, Alexis Boukouvalas, Qing Zhao
2019	J	`jnl`	Ordinal Bayesian Optimisation. CoRR Victor Picheny, Sattar Vakili, Artem Artemev
2019	—	`conf`	Stochastic Gradient Descent on a Tree: an Adaptive and Robust Approach to Stochastic Convex Optimization. Allerton Sattar Vakili, Sudeep Salgia, Qing Zhao
2018	J	`jnl`	Decision Variance in Online Learning. CoRR Sattar Vakili, Alexis Boukouvalas
2018	Misc	`conf`	Hierarchical Heavy Hitter Detection Under Unknown Models. ICASSP Sattar Vakili, Qing Zhao, Chang Liu, Chen-Nee Chuah
2018	J	`jnl`	Multi-Armed Bandits on Unit Interval Graphs. CoRR Xiao Xu, Sattar Vakili, Qing Zhao, Ananthram Swami
2017	J	`jnl`	Anomaly Detection in Hierarchical Data Streams under Unknown Models. CoRR Sattar Vakili, Qing Zhao, Chang Liu, Chen-Nee Chuah
2017	—	`conf`	Online learning with side information. MILCOM Xiao Xu, Sattar Vakili, Qing Zhao, Ananthram Swami
2016	J	`jnl`	Risk-Averse Multi-Armed Bandit Problems Under Mean-Variance Measure. IEEE J. Sel. Top. Signal Process. Sattar Vakili, Qing Zhao
2016	J	`jnl`	Risk-Averse Multi-Armed Bandit Problems under Mean-Variance Measure. CoRR Sattar Vakili, Qing Zhao
2015	—	`conf`	Bayesian quickest short-term voltage instability detection in power systems. CDC Sattar Vakili, Qing Zhao, Lang Tong
2015	—	`conf`	Mean-variance and value at risk in multi-armed bandit problems. Allerton Sattar Vakili, Qing Zhao
2015	Misc	`conf`	Quickest detection of short-term voltage instability with PMU measurements. ICASSP Sattar Vakili, Qing Zhao, Lang Tong
2015	Misc	`conf`	Risk-averse online learning under mean-variance measures. ICASSP Sattar Vakili, Qing Zhao
2014	Misc	`conf`	Time-varying stochastic multi-armed bandit problems. ACSSC Sattar Vakili, Qing Zhao, Yuan Zhou
2013	Misc	`conf`	Achieving complete learning in Multi-Armed Bandit problems. ACSSC Sattar Vakili, Qing Zhao
2013	J	`jnl`	Deterministic Sequencing of Exploration and Exploitation for Multi-Armed Bandit Problems. IEEE J. Sel. Top. Signal Process. Sattar Vakili, Keqin Liu, Qing Zhao
2013	Misc	`conf`	Distributed node-weighted connected dominating set problems. ACSSC Sattar Vakili, Qing Zhao