Understand deep learning, the nuances of its different models, and where these models can be applied. The abundance of … them image and speech recognition. Introduction to Deep Learning Using R provides a theoretical and practical understanding … of the models that perform these tasks by building upon the fundamentals of data science through machine learning and …

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving … optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via … API, Q-P-Learning, actor-critics, and learning automata · A special examination of neural-network-based function …

This book places knowledge, learning and innovation at the heart of cross-sector collaborations. Collaboration for … necessary for firms to share knowledge and innovation through a process of learning. The book contributes to this by providing … dimensions of knowledge, learning and innovation and discusses how collaboration can be created, sustained, and expanded …

Collective knowledge and the associated concepts of collectively learning, remembering and inventing are increasingly …

Using an experimental approach, Maximilian Eberl evaluates the role of implicit learning (CBM/AAT) for the modification … implicit learning for the replication of routines. Finally, the time perspective highlights the contributions of implicit … learning strategies for change in and of routines, as well as the contributions of implicit learning to deal with the path …

Preface -- PART 1: INDIVIDUAL LEARNING. Cultural differences in learning approaches; Tempelaar, Bart Rienties, Bas … Giesbers, Sybrand Schim van der Loeff -- Learning Styles and VSC Modules: A Statistical Analysis of Perceived and Actual …: GROUP LEARNING. Bringing Virtual Teams and Cross-Cultural Business Education into the Classroom; Rémy Magnier …