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NECO
2007
127views more  NECO 2007»
15 years 1 months ago
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Joseph F. Murray, Kenneth Kreutz-Delgado
STOC
2000
ACM
174views Algorithms» more  STOC 2000»
15 years 6 months ago
Noise-tolerant learning, the parity problem, and the statistical query model
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
Avrim Blum, Adam Kalai, Hal Wasserman
SIGSOFT
2005
ACM
16 years 2 months ago
KenyaEclipse: learning to program in eclipse
A fundamental part of a Computer Science degree is learning to program. Rather than starting students on a full commercial language, we favour using a dedicated "teaching lan...
Robert Chatley, Thomas Timbul
151
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ACCV
2006
Springer
15 years 3 months ago
Learning Multi-category Classification in Bayesian Framework
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
Atul Kanaujia, Dimitris N. Metaxas
COGSCI
2010
125views more  COGSCI 2010»
15 years 2 months ago
A Probabilistic Computational Model of Cross-Situational Word Learning
Words are the essence of communication: they are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisiti...
Afsaneh Fazly, Afra Alishahi, Suzanne Stevenson