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» Machine Learning, Machine Vision, and the Brain
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CVPR
2010
IEEE
15 years 7 months ago
Large-Scale Image Categorization with Explicit Data Embedding
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Florent Perronnin, Jorge Sanchez, Yan Liu
MLDM
2001
Springer
15 years 8 months ago
Learning XML Grammars
0 Temporal Abstractions and Case-Based Reasoning for Medical Course Data: Two Prognostic Applications R. Schmidt and R. Gierl University of Rostock, Germany 9.00-9.30 Local Learnin...
Henning Fernau
COGSCI
2002
99views more  COGSCI 2002»
15 years 4 months ago
Learning words from sights and sounds: a computational model
This paper presents an implemented computational model of word acquisition which learns directly from raw multimodal sensory input. Set in an information theoretic framework, the ...
Deb Roy, Alex Pentland
ICML
2010
IEEE
15 years 5 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
ICMLA
2010
15 years 2 months ago
Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
Abstract--Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as s...
Drausin Wulsin, Justin Blanco, Ram Mani, Brian Lit...