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A Flexible Solution for Sparse Learning with L0 Regularization

by instadatahelp | Aug 31, 2023 | AI Blogs

L0Learn: A Scalable Package for Sparse Learning using L0 Regularization Hussein Hazimeh, Rahul Mazumder, Tim Nonet; 24(205):1−8, 2023. Abstract This article introduces L0Learn, an open-source package designed for sparse linear regression and classification using L0...
Mediators’ Feedback on the Article “Pure Exploration” (arXiv:2308.15552v1 [cs.LG])

Mediators’ Feedback on the Article “Pure Exploration” (arXiv:2308.15552v1 [cs.LG])

by instadatahelp | Aug 31, 2023 | AI Blogs

In this work, we introduce a new version of the best-arm identification problem called best-arm identification under mediators’ feedback (BAI-MF). In traditional BAI problems, the goal is to find the arm with the highest expected reward. However, this framework...

Conditions Required for Inverse Reinforcement Learning of Bayesian Stopping Time Problems

by instadatahelp | Aug 31, 2023 | AI Blogs

Necessary and Sufficient Conditions for Inverse Reinforcement Learning of Bayesian Stopping Time Problems Authors: Kunal Pattanayak, Vikram Krishnamurthy; Volume 24, Issue 52, Pages 1-64, 2023 Abstract This paper introduces a framework for inverse reinforcement...
Mediators’ Feedback on the Article “Pure Exploration” (arXiv:2308.15552v1 [cs.LG])

Adversarial Style Transfer Enhances Robust Policy Optimization in Deep Reinforcement Learning

by instadatahelp | Aug 31, 2023 | AI Blogs

[Submitted on 29 Aug 2023] Click here to download a PDF of the paper titled “Adversarial Style Transfer for Robust Policy Optimization in Deep Reinforcement Learning” by Md Masudur Rahman and Yexiang Xue: Download PDF Abstract: This paper presents an...

Online Learning with Memory and Non-stochastic Control in Non-stationary Environments

by instadatahelp | Aug 31, 2023 | AI Blogs

Non-stationary Online Learning with Memory and Non-stochastic Control Peng Zhao, Yu-Hu Yan, Yu-Xiang Wang, Zhi-Hua Zhou; 24(206):1−70, 2023. Abstract This paper investigates the problem of Online Convex Optimization (OCO) with memory, which allows loss functions to...
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