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» LEO - DB2's LEarning Optimizer
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JMLR
2012
11 years 10 months ago
Marginal Regression For Multitask Learning
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Mladen Kolar, Han Liu
ICASSP
2008
IEEE
14 years 2 months ago
Learning the kernel via convex optimization
The performance of a kernel-based learning algorithm depends very much on the choice of the kernel. Recently, much attention has been paid to the problem of learning the kernel it...
Seung-Jean Kim, Argyrios Zymnis, Alessandro Magnan...
JMLR
2012
11 years 10 months ago
Deterministic Annealing for Semi-Supervised Structured Output Learning
In this paper we propose a new approach for semi-supervised structured output learning. Our approach uses relaxed labeling on unlabeled data to deal with the combinatorial nature ...
Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Be...
COLING
2010
13 years 2 months ago
Broad Coverage Multilingual Deep Sentence Generation with a Stochastic Multi-Level Realizer
Most of the known stochastic sentence generators use syntactically annotated corpora, performing the projection to the surface in one stage. However, in full-fledged text generati...
Bernd Bohnet, Leo Wanner, Simon Mille, Alicia Burg...
AGI
2011
12 years 11 months ago
Coherence Progress: A Measure of Interestingness Based on Fixed Compressors
The ability to identify novel patterns in observations is an essential aspect of intelligence. In a computational framework, the notion of a pattern can be formalized as a program ...
Tom Schaul, Leo Pape, Tobias Glasmachers, Vincent ...