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» Learning to learn with the informative vector machine
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NIPS
2004
13 years 10 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
PRL
2007
100views more  PRL 2007»
13 years 8 months ago
Visible models for interactive pattern recognition
The bottleneck in interactive visual classification is the exchange of information between human and machine. We introduce the concept of the visible model, which is an ion of an ...
Jie Zou, George Nagy
ICML
2006
IEEE
14 years 10 months ago
Online decoding of Markov models under latency constraints
The Viterbi algorithm is an efficient and optimal method for decoding linear-chain Markov Models. However, the entire input sequence must be observed before the labels for any tim...
Mukund Narasimhan, Paul A. Viola, Michael Shilman
ICMI
2009
Springer
162views Biometrics» more  ICMI 2009»
14 years 3 months ago
Multi-modal features for real-time detection of human-robot interaction categories
Social interactions unfold over time, at multiple time scales, and can be observed through multiple sensory modalities. In this paper, we propose a machine learning framework for ...
Ian R. Fasel, Masahiro Shiomi, Pilippe-Emmanuel Ch...
CVPR
2006
IEEE
14 years 11 months ago
A Generative-Discriminative Hybrid Method for Multi-View Object Detection
We present a novel discriminative-generative hybrid approach in this paper, with emphasis on application in multiview object detection. Our method includes a novel generative mode...
DongQing Zhang, Shih-Fu Chang