Sattar Vakili

Orcid: 0000-0001-7085-1191

According to our database1, Sattar Vakili authored at least 50 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Collaborative Learning in Kernel-Based Bandits for Distributed Users.
IEEE Trans. Signal Process., 2023

Optimal Regret Bounds for Collaborative Learning in Bandits.
CoRR, 2023

Robust Best-arm Identification in Linear Bandits.
CoRR, 2023

Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency.
CoRR, 2023

Adversarial Contextual Bandits Go Kernelized.
CoRR, 2023

Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow.
CoRR, 2023

Kernelized Reinforcement Learning with Order Optimal Regret Bounds.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Information Gain and Uniform Generalization Bounds for Neural Kernel Models.
Proceedings of the IEEE International Symposium on Information Theory, 2023

Delayed Feedback in Kernel Bandits.
Proceedings of the International Conference on Machine Learning, 2023

Image generation with shortest path diffusion.
Proceedings of the International Conference on Machine Learning, 2023

Fisher-Legendre (FishLeg) optimization of deep neural networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Generative Diffusion Models for Radio Wireless Channel Modelling and Sampling.
Proceedings of the IEEE Global Communications Conference, 2023

Sample Complexity of Kernel-Based Q-Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Kernel-based Federated Learning with Personalization.
CoRR, 2022

Provably and Practically Efficient Neural Contextual Bandits.
CoRR, 2022

Near-Optimal Collaborative Learning in Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning.
Proceedings of the International Conference on Machine Learning, 2022

2021
Uniform Generalization Bounds for Overparameterized Neural Networks.
CoRR, 2021

Scalable Thompson Sampling using Sparse Gaussian Process Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Optimal Order Simple Regret for Gaussian Process Bandits.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Open Problem: Tight Online Confidence Intervals for RKHS Elements.
Proceedings of the Conference on Learning Theory, 2021

Gambler Bandits and the Regret of Being Ruined.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

On Information Gain and Regret Bounds in Gaussian Process Bandits.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Multi-Armed Bandits on Partially Revealed Unit Interval Graphs.
IEEE Trans. Netw. Sci. Eng., 2020

A Computationally Efficient Approach to Black-box Optimization using Gaussian Process Models.
CoRR, 2020

Scalable Thompson Sampling using Sparse Gaussian Process Models.
CoRR, 2020

Amortized variance reduction for doubly stochastic objectives.
CoRR, 2020

Regret Bounds for Noise-Free Bayesian Optimization.
CoRR, 2020

Amortized variance reduction for doubly stochastic objective.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Ordinal Bayesian Optimisation.
CoRR, 2019

A Random Walk Approach to First-Order Stochastic Convex Optimization.
Proceedings of the IEEE International Symposium on Information Theory, 2019

Adaptive Sensor Placement for Continuous Spaces.
Proceedings of the 36th International Conference on Machine Learning, 2019

Decision Variance in Risk-Averse Online Learning.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Stochastic Gradient Descent on a Tree: an Adaptive and Robust Approach to Stochastic Convex Optimization.
Proceedings of the 57th Annual Allerton Conference on Communication, 2019

2018
Decision Variance in Online Learning.
CoRR, 2018

Multi-Armed Bandits on Unit Interval Graphs.
CoRR, 2018

Hierarchical Heavy Hitter Detection Under Unknown Models.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017
Anomaly Detection in Hierarchical Data Streams under Unknown Models.
CoRR, 2017

Online learning with side information.
Proceedings of the 2017 IEEE Military Communications Conference, 2017

2016
Risk-Averse Multi-Armed Bandit Problems Under Mean-Variance Measure.
IEEE J. Sel. Top. Signal Process., 2016

2015
Quickest detection of short-term voltage instability with PMU measurements.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Risk-averse online learning under mean-variance measures.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Bayesian quickest short-term voltage instability detection in power systems.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Mean-variance and value at risk in multi-armed bandit problems.
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015

2014
Time-varying stochastic multi-armed bandit problems.
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2013
Deterministic Sequencing of Exploration and Exploitation for Multi-Armed Bandit Problems.
IEEE J. Sel. Top. Signal Process., 2013

Achieving complete learning in Multi-Armed Bandit problems.
Proceedings of the 2013 Asilomar Conference on Signals, 2013

Distributed node-weighted connected dominating set problems.
Proceedings of the 2013 Asilomar Conference on Signals, 2013


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