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Sattar Vakili
Sattar Vakili
MediaTek Research
Verified email at mtkresearch.com - Homepage
Title
Cited by
Cited by
Year
On information gain and regret bounds in gaussian process bandits
S Vakili, K Khezeli, V Picheny
International Conference on Artificial Intelligence and Statistics, 82-90, 2021
1332021
Deterministic sequencing of exploration and exploitation for multi-armed bandit problems
S Vakili, K Liu, Q Zhao
IEEE Journal of Selected Topics in Signal Processing 7 (5), 759-767, 2013
1312013
Risk-averse multi-armed bandit problems under mean-variance measure
S Vakili, Q Zhao
IEEE Journal of Selected Topics in Signal Processing 10 (6), 1093-1111, 2016
1102016
Optimal order simple regret for Gaussian process bandits
S Vakili, N Bouziani, S Jalali, A Bernacchia, D Shiu
Advances in Neural Information Processing Systems 34, 21202-21215, 2021
452021
Mean-variance and value at risk in multi-armed bandit problems
S Vakili, Q Zhao
2015 53rd Annual Allerton Conference on Communication, Control, and …, 2015
452015
Scalable Thompson Sampling using Sparse Gaussian Process Models
S Vakili, H Moss, A Artemev, V Dutordoir, V Picheny
Advances in Neural Information Processing Systems 34, 2021
422021
A domain-shrinking based bayesian optimization algorithm with order-optimal regret performance
S Salgia, S Vakili, Q Zhao
Advances in Neural Information Processing Systems 34, 28836-28847, 2021
392021
Open problem: Tight online confidence intervals for RKHS elements
S Vakili, J Scarlett, T Javidi
Conference on Learning Theory, 4647-4652, 2021
242021
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning
S Vakili, J Scarlett, D Shiu, A Bernacchia
International Conference on Machine Learning (ICML), 2022
232022
Near-Optimal Collaborative Learning in Bandits
C Réda, S Vakili, E Kaufmann
Advances in Neural Information Processing Systems (NeurIPS), 2022
212022
Information gain and uniform generalization bounds for neural kernel models
S Vakili, M Bromberg, J Garcia, D Shiu, A Bernacchia
2023 IEEE International Symposium on Information Theory (ISIT), 555-560, 2023
19*2023
Adaptive sensor placement for continuous spaces
JA Grant, A Boukouvalas, RR Griffiths, DS Leslie, S Vakili, EM De Cote
http://proceedings.mlr.press/v97/grant19a.html 97, 2385-2393, 2019
192019
Open Problem: Regret Bounds for Noise-Free Kernel-Based Bandits
S Vakili
Conference on Learning Theory, 2022, 2022
15*2022
Trieste: Efficiently exploring the depths of black-box functions with TensorFlow
V Picheny, J Berkeley, HB Moss, H Stojic, U Granta, SW Ober, A Artemev, ...
arXiv preprint arXiv:2302.08436, 2023
132023
A random walk approach to first-order stochastic convex optimization
S Vakili, Q Zhao
2019 IEEE International Symposium on Information Theory (ISIT), 395-399, 2019
122019
Fisher-Legendre (FishLeg) optimization of deep neural networks
JR Garcia, F Freddi, S Fotiadis, M Li, S Vakili, A Bernacchia, G Hennequin
The Eleventh International Conference on Learning Representations, 2023
112023
Hierarchical heavy hitter detection under unknown models
S Vakili, Q Zhao, C Liu, CN Chuah
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
112018
Achieving complete learning in multi-armed bandit problems
S Vakili, Q Zhao
2013 Asilomar Conference on Signals, Systems and Computers, 1778-1782, 2013
102013
Risk-averse online learning under mean-variance measures
S Vakili, Q Zhao
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
92015
Time-varying stochastic multi-armed bandit problems
S Vakili, Q Zhao, Y Zhou
2014 48th Asilomar Conference on Signals, Systems and Computers, 2103-2107, 2014
92014
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