The system presented in this book consists of two more-or-less independent parts. The first is the system's parallel network memory scheme; the second part of the knowledge-base …
A description of perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical guarantees.In nearly all machine learning, …
An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities.The interplay between optimization and …
How we can get more joy from our machines by telling them what our hearts desire.In this informative, accessible, and very funny book, Michael L. Littman inspires readers to learn …
State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.Machine learning develops intelligent computer systems that …
What can humans do? What can machines do? How do humans delegate actions to machines? In this book, Harry Collins and Martin Kusch combine insights from sociology and philosophy to …
To date, books on object-oriented programming have focused either on the methodology of the object-oriented paradigm or on teaching the details of a particular programming …
If machine learning transforms the nature of knowledge, does it also transform the practice of critical thought?Machine learning-programming computers to learn from data-has spread …
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning …
August 8-12, 1994, Brighton, England From Animals to Animats 3 brings together research intended to advance the front tier of an exciting new approach to understanding …
