Journal ArticleDOI
Learning from delayed rewards
TLDR
The invention relates to a circuit for use in a receiver which can receive two-tone/stereo signals which is intended to make a choice between mono or stereo reproduction of signal A or of signal B and vice versa.About:
This article is published in Robotics and Autonomous Systems.The article was published on 1995-10-01. It has received 2861 citations till now. The article focuses on the topics: Autonomous system (mathematics) & Robotics.read more
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Book ChapterDOI
Teaching Machine Learning to Design Students
Bram van der Vlist,Rick Westelaken,Christoph Bartneck,Jun Hu,Rene Ahn,Emilia I. Barakova,Frank Delbressine,Loe Feijs +7 more
TL;DR: This work successfully used the Embodied Intelligence method to teach machine learning to students, embodying the learning system into the Lego Mindstorm NXT platform to provide the student with a tangible tool to understand and interact with a learning system.
Proceedings ArticleDOI
Simulation Studies of Multi-armed Bandits with Covariates (Invited Paper)
TL;DR: In this paper, the authors evaluate the performance of a number of action selection methods on the multi-armed bandit problem with covariates and show that there is a trade-off between the satisfaction of the different performance measures.
Book ChapterDOI
A Gentle Introduction to Reinforcement Learning
TL;DR: This paper provides a gentle introduction to some of the basics of reinforcement learning, as well as pointers to more advanced topics within the field.
Journal ArticleDOI
Reinforced contrast adaptation
TL;DR: It is demonstrated that Reinforcement Learning is a potential method for solving the problem of subjective evaluation of human operators and an agent is developed that uses the Q-learning algorithm.
Proceedings ArticleDOI
NPAS: A Compiler-aware Framework of Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration
Zhengang Li,Geng Yuan,Wei Niu,Pu Zhao,Yanyu Li,Yuxuan Cai,Xuan Shen,Zheng Zhan,Zhenglun Kong,Qing Jin,Zhiyu Chen,Sijia Liu,Kaiyuan Yang,Bin Ren,Yanzhi Wang,Xue Lin +15 more
TL;DR: A general category of fine-grained structured pruning applicable to various DNN layers is proposed, and a comprehensive, compiler automatic code generation framework supporting different DNNs and different pruning schemes are proposed, which bridge the gap of model compression and NAS.
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