This collection covers the state of the art in automatic differentiation theory and practice. Practitioners and students ...
WeiterlesenThis work, a tribute to renowned researcher Robert Paige, is a collection of revised papers published in his honor in the ...
WeiterlesenComputer science will be radically transformed if ongoing efforts to build large-scale quantum computers eventually succeed ...
WeiterlesenComputer science will be radically transformed if ongoing efforts to build large-scale quantum computers eventually succeed ...
WeiterlesenThis book brings together leading academic researchers and industrial practitioners to address the issues in this emerging ...
WeiterlesenSearching in a large database of videos is one of the challenges faced by the user today as most of the results are inaccurate ...
WeiterlesenThis book constitutes the refereed proceedings of the Third International Conference on Autonomic and Trusted Computing, ...
WeiterlesenMAS offiers powerful metaphors for information system conceptualization, a range of new techniques, and technologies specifically ...
WeiterlesenMAS offiers powerful metaphors for information system conceptualization, a range of new techniques, and technologies specifically ...
WeiterlesenThis book deals with the theoretical and methodological aspects of incorporating intelligence in Autonomous Robots and Agents. ...
WeiterlesenThe International Workshop on "Autonomous Systems - Self-Organization, Management, and Control " is the eighth in a successful ...
WeiterlesenThe contents of this book builds further on the contents of the first volume in the Philips Research Book Series, Battery ...
WeiterlesenR's open source nature, free availability, and large number of contributor packages have made R the software of choice for ...
WeiterlesenProbabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. ...
WeiterlesenProbabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. ...
WeiterlesenBayesian Reliability presents modern methods and techniques for analyzing reliability data from a Bayesian perspective. The ...
WeiterlesenStats with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from ...
WeiterlesenTeaches you tools that you can use to build efficient applications. It starts with an introduction to algorithms and big ...
WeiterlesenThere are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve ...
WeiterlesenCombines experimental and theoretical research on big data recommender systems to help computer scientists develop new concepts ...
Weiterlesen