This open access proceedings volume brings selected, peer-reviewed contributions presented at the Third Stochastic Transport in Upper Ocean Dynamics (STUOD) 2022 Workshop, held virtually and in person at the Imperial College London, UK, September 26–29, 2022. The STUOD project is supported by an ERC Synergy Grant, and led by Imperial College London, the National Institute for Research in Comp…
In this work, Marcin Milkowski argues that the mind can be explained computationally because it is itself computational - whether it engages in mental arithmetic, parses natural language, or processes the auditory signals that allow us to experience music.OCLC-licensed vendor bibliographic record.
"A Bradford book.""Using the tools of complexity theory, Stephen Judd develops a formal description of associative learning in connectionist networks. He rigorously exposes the computational difficulties in training neural networks and explores how certain design principles will or will not make the problems easier. Judd looks beyond the scope of any one particular learning rule, at a level abo…
Neural networks usually work adequately on small problems but can run into trouble when they are scaled up to problems involving large amounts of input data. Circuit Complexity and Neural Networks addresses the important question of how well neural networks scale - that is, how fast the computation time and number of neurons grow as the problem size increases. It surveys recent research in circ…
Communication Complexity describes a new intuitive model for studying circuit networks that captures the essence of circuit depth. Although the complexity of boolean functions has been studied for almost 4 decades, the main problems the inability to show a separation of any two classes, or to obtain nontrivial lower bounds remain unsolved. The communication complexity approach provides clues as…
OCLC-licensed vendor bibliographic record.
"Reprinted from Artificial intelligence, volume 72, numbers 1-2 (January 1995) and volume 73, numbers 1-2 (February 1995)"--Title page verso.Over time the field of artificial intelligence has developed an "agent perspective" expanding its focus from thought to action, from search spaces to physical environments, and from problem-solving to long-term activity. Originally published as a special d…
"Noam Nisan is Lecturer in the Department of Computer Science at Hebrew University in Jerusalem. He received his doctoral degree from the University of California, Berkeley.""Randomization is an important tool in the design of algorithms, and the ability of randomization to provide enhanced power is a major research topic in complexity theory. Noam Nisan continues the investigation into the pow…
"In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of 'choice points' that life scientists confront in developing mechanistic…
This book constitutes the thoroughly refereed proceedings of the 11th International Conference on Web and Internet Economics, WINE 2015, held in Amsterdam, The Netherlands, in December 2015. The 30 regular papers presented together with 8 abstracts were carefully reviewed and selected from 142 submissions and cover results on incentives and computation in theoretical computer science, artificia…