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» Learning from measurements in exponential families
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BIBM
2010
IEEE
139views Bioinformatics» more  BIBM 2010»
13 years 4 months ago
Scalable, updatable predictive models for sequence data
The emergence of data rich domains has led to an exponential growth in the size and number of data repositories, offering exciting opportunities to learn from the data using machin...
Neeraj Koul, Ngot Bui, Vasant Honavar
TIT
2002
78views more  TIT 2002»
13 years 7 months ago
Tradeoffs between the excess-code-length exponent and the excess-distortion exponent in lossy source coding
Lossy compression of a discrete memoryless source (DMS) with respect to a single-letter distortion measure is considered. We study the best attainable tradeoff between the exponent...
Tsachy Weissman, Neri Merhav
IEICET
2010
80views more  IEICET 2010»
13 years 5 months ago
Theoretical Analysis of Density Ratio Estimation
Density ratio estimation has gathered a great deal of attention recently since it can be used for various data processing tasks. In this paper, we consider three methods of densit...
Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama
IBPRIA
2009
Springer
14 years 10 hour ago
Large Scale Online Learning of Image Similarity through Ranking
ent abstract presents OASIS, an Online Algorithm for Scalable Image Similarity learning that learns a bilinear similarity measure over sparse representations. OASIS is an online du...
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio
ICML
2009
IEEE
14 years 8 months ago
Learning Markov logic network structure via hypergraph lifting
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
Stanley Kok, Pedro Domingos