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ISNN
2011
Springer
14 years 9 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
BSN
2011
IEEE
233views Sensor Networks» more  BSN 2011»
14 years 6 months ago
Compressive Sensing of Neural Action Potentials Using a Learned Union of Supports
—Wireless neural recording systems are subject to stringent power consumption constraints to support long-term recordings and to allow for implantation inside the brain. In this ...
Zainul Charbiwala, Vaibhav Karkare, Sarah Gibson, ...
CVPR
2004
IEEE
16 years 8 months ago
Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting
We assess the applicability of several popular learning methods for the problem of recognizing generic visual categories with invariance to pose, lighting, and surrounding clutter...
Fu Jie Huang, Léon Bottou, Yann LeCun
BERTINORO
2005
Springer
16 years 4 days ago
Emergent Consensus in Decentralised Systems Using Collaborative Reinforcement Learning
Abstract. This paper describes the application of a decentralised coordination algorithm, called Collaborative Reinforcement Learning (CRL), to two different distributed system pr...
Jim Dowling, Raymond Cunningham, Anthony Harringto...
IUI
2003
ACM
15 years 12 months ago
Lessons learned in modeling schizophrenic and depressed responsive virtual humans for training
This paper describes lessons learned in developing the linguistic, cognitive, emotional, and gestural models underlying virtual human behavior in a training application designed t...
Robert C. Hubal, Geoffrey A. Frank, Curry I. Guinn