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ICML
2007
IEEE
15 years 10 months ago
Transductive support vector machines for structured variables
We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over a...
Alexander Zien, Ulf Brefeld, Tobias Scheffer
ICML
2004
IEEE
15 years 10 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
ICCV
2011
IEEE
13 years 10 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
IMCSIT
2010
14 years 8 months ago
Semi-Automatic Extension of Morphological Lexica
Abstract--We present a tool that facilitates the efficient extension of morphological lexica. The tool exploits information from a morphological lexicon, a morphological grammar an...
Tobias Kaufmann, Beat Pfister
IBPRIA
2009
Springer
15 years 2 months 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