Abstract: Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6731005 ...

Abstract: Recently, we have witnessed impressive achievements in cancer survival analysis by integrating multimodal data, e.g., pathology images and genomic profiles. However, the heterogeneity and ...

Abstract: Localized scatterers can be expected to give rise to spatial variations in the electric field and in the current distribution. The transport equation allowing for spatial variations is ...

Book Abstract: The first systematic presentation of electricity market design-from the basics to the cutting edge. Unique in its breadth and depth. Using examples and focusing on fundamentals, it ...

Abstract: Time series classification is an important task in time series data mining, and has attracted great interests and tremendous efforts during last decades. However, it remains a challenging ...

Book Abstract: An expert guide to understanding and making optimum use of BSIM Used by more chip designers worldwide than any other comparable model, the Berkeley Short-Channel IGFET Model (BSIM) has, ...

Book Abstract: This comprehensive guide offers a detailed treatment of the analysis, design, simulation and testing of the full range of today's leading delta-sigma data converters. Written by ...

Book Abstract: This comprehensive textbook introduces electrical engineers to the most relevant concepts and techniques in electric power systems engineering today. With an emphasis on practical ...

Abstract: Two machine-learning procedures have been investigated in some detail using the game of checkers. Enough work has been done to verify the fact that a computer can be programmed so that it ...

Abstract: This chapter contains sections titled: The Problem, The Generalized Delta Rule, Simulation Results, Some Further Generalizations, Conclusion ...

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