Optimization
Stochastic Multiple Target Sampling Gradient Descent
A natural question then arises: " Can we derive a probabilistic
Checklist
The checklist follows the references. For example: Did you include the license to the code and datasets? Did you include the license to the code and datasets? Did you include the license to the code and datasets? Please do not modify the questions and only use the provided macros for your answers.
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity William de V azelhes
Hard-thresholding gradient descent is a dominant technique to solve this problem.
Optimal Order Simple Regret for Gaussian Process Bandits
That is a ubiquitous problem in academic research and industrial production.
Semialgebraic Optimization for Lipschitz Constants of ReLU Networks
We introduce a semidefinite programming hierarchy to estimate the global and local Lipschitz constant of a multiple layer deep neural network.
Efficient Planning in Large MDPs with Weak Linear Function Approximation
Roshan Shariff & Csaba Szepesvári
In this paper we consider the intersection of these two problem formulations.
Accelerating Quadratic Optimization with Reinforcement Learning
Solving quadratic programs (QPs) efficiently is critical to applications in finance, robotic control and operations research.