Sattar Vakili
24 papers · 2019–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Renaissance Researcher (5) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (11) π Conference Polyglot (7)
π£
Hot Topic Early Bird
π
Renaissance Researcher
(5)
π
Conference Polyglot
(7)
π
Triple Crown
ποΈ
Keyword Collector
(66)
β‘
Prolific Year
(5)
π
Century Club
(24)
π₯
Unstoppable
(7)
Conferences
ICML (8)
NIPS (6)
AISTATS (3)
COLT (3)
ALT (2)
ICLR (1)
UAI (1)
Top co-authors
Keywords
regret bound
(10)
bayesian optimization
(5)
kernel methods
(5)
gaussian process
(5)
kernel ridge regression
(4)
reinforcement learning
(3)
reproducing kernel hilbert space
(3)
function approximation
(3)
confidence interval
(2)
sample complexity
(2)
information gain
(2)
collaborative learning
(2)
markov decision process
(2)
regret minimization
(2)
sparse approximation
(2)
multi-armed bandit
(2)
stochastic optimization
(2)
variational inference
(2)
thompson sampling
(2)
black-box optimization
(1)
Papers
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
ICML 2025
Near-Optimal Sample Complexity in Reward-Free Kernel-based Reinforcement Learning
AISTATS 2025
Reward-Free Kernel-Based Reinforcement Learning
ICML 2024
Adversarial Contextual Bandits Go Kernelized
ALT 2024
Optimal Regret Bounds for Collaborative Learning in Bandits
ALT 2024
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
NIPS 2024
Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning
COLT 2024
Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
ICML 2024
Image generation with shortest path diffusion
ICML 2023
Delayed Feedback in Kernel Bandits
ICML 2023
Sample Complexity of Kernel-Based Q-Learning
AISTATS 2023
Kernelized Reinforcement Learning with Order Optimal Regret Bounds
NIPS 2023
Fisher-Legendre (FishLeg) optimization of deep neural networks
ICLR 2023
Near-Optimal Collaborative Learning in Bandits
NIPS 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning
ICML 2022
Open Problem: Regret Bounds for Noise-Free Kernel-Based Bandits
COLT 2022
Scalable Thompson Sampling using Sparse Gaussian Process Models
NIPS 2021
Optimal Order Simple Regret for Gaussian Process Bandits
NIPS 2021
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance
NIPS 2021
On Information Gain and Regret Bounds in Gaussian Process Bandits
AISTATS 2021
Open Problem: Tight Online Confidence Intervals for RKHS Elements
COLT 2021
Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization
ICML 2020
Amortized variance reduction for doubly stochastic objective
UAI 2020
Adaptive Sensor Placement for Continuous Spaces
ICML 2019