Results 91 to 100 of about 102,050 (305)
Reinforcement learning in large state action spaces
, 2023 Reinforcement learning (RL) is a promising framework for training intelligent agents which learn to optimize long term utility by directly interacting with the environment.
Mahajan, Anuj
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A systematic review of learning theory on computational thinking
, 2020 Link to publisher's homepage at https://johdec.unimap.edu.my/This paper reviews systematically theory used in the past studies on computational thinking, learning theory used in past studies on computational thinking and explore how these learning ...
Wan Ahmad Jaafar, Wan Yahaya +1 more
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An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials
Advanced Engineering Materials, EarlyView.An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut +16 more
wiley +1 more source
Adaptation for Regularization Operators in Learning Theory [PDF]
, 2006 We consider learning algorithms induced by regularization methods in the regression setting. We show that previously obtained error bounds for these algorithms using a-priori choices of the regularization parameter, can be attained using a suitable a ...
Andrea Caponnetto +3 more
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A Dislocation Perspective on Strength and Toughness in Ceramics
Advanced Engineering Materials, EarlyView.Dislocations in ceramics enjoy a long but yet under‐appreciated history. The three research waves for dislocations in ceramics highlight the topic evolution over the last 90 years. This review focuses on the impact of dislocation on strength and toughness in ceramics.
Xufei Fang
wiley +1 more source
Why Philosophers Should Care About Computational Complexity
, 2011 One might think that, once we know something is computable, how efficiently it can be computed is a practical question with little further philosophical importance. In this essay, I offer a detailed case that one would be wrong.
Scott Aaronson, Aaronson, Scott
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Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
Advanced Functional Materials, EarlyView.A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou +5 more
wiley +1 more source
Humanities & Social Sciences CommunicationsThis study explored the relationships among programming self-efficacy, learning strategies, and computational thinking on the basis of self-regulation theory.
Qi Li +4 more
doaj +1 more source
Computational Theories of Curiosity-Driven Learning
, 2018 What are the functions of curiosity? What are the mechanisms of curiosity-driven learning?We approach these questions about the living using concepts and tools from machine learning and developmental robotics. We argue that curiosity-driven learning enables organisms to make discoveries to solve complex problems with rare or deceptive rewards.
openaire +4 more sources
Designed Lewis Acid–Base Passivation for High Performance Perovskite Solar Cells
Advanced Functional Materials, EarlyView.ABSTRACT Silicon's high cost and long energy payback time remain major barriers to the global expansion of solar power. In contrast, metal–halide perovskites offer abundant, solution‐processable absorbers, and have achieved efficiencies of 25%–30%, positioning them as strong competitors to silicon.
Afna Manaf +4 more
wiley +1 more source