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JMLR
2010
155views more  JMLR 2010»
13 years 7 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
EJASP
2010
89views more  EJASP 2010»
13 years 3 months ago
Sparsity-Aware Estimation of CDMA System Parameters
The number of active users, their timing offsets, and their (possibly dispersive) channels with the access point are decisive parameters for wireless code division multiple access...
Daniele Angelosante, Emanuele Grossi, Georgios B. ...
JMLR
2010
103views more  JMLR 2010»
13 years 3 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
13 years 15 days 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
13 years 9 days 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