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Neural Information Processing series

An overview of recent work in the field of structured prediction, the building of predictive machine learning models for interrelated and dependent outputs.

Key approaches in the rapidly developing area of sparse modeling, focusing on its application in fields including neuroscience, computational biology, and computer vision.

An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities.

State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

The latest research in the development of technologies that will allow humans to communicate, using brain signals only, with computers, wheelchairs, prostheses, and other devices.