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JMLR
2010
103views more  JMLR 2010»
13 years 1 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
ACL
2011
12 years 10 months ago
Jointly Learning to Extract and Compress
We learn a joint model of sentence extraction and compression for multi-document summarization. Our model scores candidate summaries according to a combined linear model whose fea...
Taylor Berg-Kirkpatrick, Dan Gillick, Dan Klein
ICANN
2011
Springer
12 years 10 months ago
Semi-supervised Learning for WLAN Positioning
Currently the most accurate WLAN positioning systems are based on the fingerprinting approach, where a “radio map” is constructed by modeling how the signal strength measureme...
Teemu Pulkkinen, Teemu Roos, Petri Myllymäki
IJON
2000
104views more  IJON 2000»
13 years 6 months ago
Harmonic analysis of spiking neuronal pairs
Harmonic analysis is applied to analyze the transmission of bandlimited signals via spike trains generated by a pair of leaky integrate-and-fire (LIF) model neurons organized in a...
Charles H. Anderson, Qingfeng Huang, John W. Clark
ECCV
2002
Springer
14 years 8 months ago
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
Hedvig Sidenbladh, Michael J. Black, Leonid Sigal