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2017


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Design of a visualization scheme for functional connectivity data of Human Brain

Bramlage, L.

Hochschule Osnabrück - University of Applied Sciences, 2017 (thesis)

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Bramlage_BSc_2017.pdf [BibTex]

2017


2006


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Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference

Weiss, Y., Schölkopf, B., Platt, J.

Proceedings of the 19th Annual Conference on Neural Information Processing Systems (NIPS 2005), pages: 1676, MIT Press, Cambridge, MA, USA, 19th Annual Conference on Neural Information Processing Systems (NIPS), May 2006 (proceedings)

Abstract
The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees--physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only twenty-five percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains the papers presented at the December 2005 meeting, held in Vancouver.

ei

Web [BibTex]

2006


Web [BibTex]


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Machine Learning Challenges: evaluating predictive uncertainty, visual object classification and recognising textual entailment

Quinonero Candela, J., Dagan, I., Magnini, B., Lauria, F.

Proceedings of the First Pascal Machine Learning Challenges Workshop on Machine Learning Challenges, Evaluating Predictive Uncertainty, Visual Object Classification and Recognizing Textual Entailment (MLCW 2005), pages: 462, Lecture Notes in Computer Science, Springer, Heidelberg, Germany, First Pascal Machine Learning Challenges Workshop (MLCW), 2006 (proceedings)

Abstract
This book constitutes the thoroughly refereed post-proceedings of the First PASCAL (pattern analysis, statistical modelling and computational learning) Machine Learning Challenges Workshop, MLCW 2005, held in Southampton, UK in April 2005. The 25 revised full papers presented were carefully selected during two rounds of reviewing and improvement from about 50 submissions. The papers reflect the concepts of three challenges dealt with in the workshop: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; the second challenge was to recognize objects from a number of visual object classes in realistic scenes; the third challenge of recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding.

ei

Web DOI [BibTex]

Web DOI [BibTex]