"How people in Costa Rica live with algorithms in their daily life"--OCLC-licensed vendor bibliographic record.
"Bonini and Trere explore how people all around the world use different tactics to interfere with the algorithms behind the platforms they use to work, entertain, and inform themselves"--OCLC-licensed vendor bibliographic record.
"Essays that look at the challenges and risks in designing algorithms and platforms for children, with an emphasis on innovative designs and solutions for algorithmic justice, learning, and equity"--OCLC-licensed vendor bibliographic record.
"Ethnographic study of the constitution of algorithms"--OCLC-licensed vendor bibliographic record.
An introduction to computational thinking that traces a genealogy beginning centuries before the digital computer. A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation; eventually, every field had a computational branch: computational physics, computational biology, computational …
Collected papers based on talks presented at two Neural Information Processing Systems workshops.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 are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must sati…
"Parallel computation will become the norm in the coming decades. Unfortunately, advances in parallel hardware have far outpaced parallel applications of software. There are currently two approaches to applying parallelism to applications. One is to write completely new applications in new languages. But abandoning applications that work is unacceptable to most nonacademic users of high-perform…
In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by…
Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifier--a limited, but well-established and comprehensively studied model--and extends its applicability to a wide range of nonlinear pattern-recognition tasks such as natural language processing, machine vision, and biological sequence analysis. This…
"A Bradford book."It is the first detailed exploration of the problem of learning action strategies in the context of designing embedded systems that adapt their behavior to a complex, changing environment; such systems include mobile robots, factory process controllers, and long-term software databases.Learning to perform complex action strategies is an important problem in the fields of artif…