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NIPS
2008
14 years 18 days ago
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...
Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Ma...
NIPS
2004
14 years 17 days ago
Multiple Alignment of Continuous Time Series
Multiple realizations of continuous-valued time series from a stochastic process often contain systematic variations in rate and amplitude. To leverage the information contained i...
Jennifer Listgarten, Radford M. Neal, Sam T. Rowei...
TSMC
2010
13 years 5 months ago
Cellular Learning Automata With Multiple Learning Automata in Each Cell and Its Applications
The cellular learning automaton (CLA), which is a4 combination of cellular automaton (CA) and learning automaton5 (LA), is introduced recently. This model is superior to CA because...
Hamid Beigy, Mohammad Reza Meybodi
ICML
2008
IEEE
15 years 1 hour ago
Multiple instance ranking
This paper introduces a novel machine learning model called multiple instance ranking (MIRank) that enables ranking to be performed in a multiple instance learning setting. The mo...
Charles Bergeron, Jed Zaretzki, Curt M. Breneman, ...
CVPR
2001
IEEE
15 years 1 months ago
Automatic Description of Buildings with Complex Rooftops from Multiple Images
We present a model-based approach to detecting and describing compositions of buildings with complex rooftops. Previous approaches have dealt with either simpler models or models ...
Zu Whan Kim, Andres Huertas, Ramakant Nevatia