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ICCV
2011
IEEE
14 years 6 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
EMNLP
2011
14 years 6 months ago
Learning Sentential Paraphrases from Bilingual Parallel Corpora for Text-to-Text Generation
Previous work has shown that high quality phrasal paraphrases can be extracted from bilingual parallel corpora. However, it is not clear whether bitexts are an appropriate resourc...
Juri Ganitkevitch, Chris Callison-Burch, Courtney ...
GECCO
2007
Springer
149views Optimization» more  GECCO 2007»
16 years 24 days ago
Modeling XCS in class imbalances: population size and parameter settings
This paper analyzes the scalability of the population size required in XCS to maintain niches that are infrequently activated. Facetwise models have been developed to predict the ...
Albert Orriols-Puig, David E. Goldberg, Kumara Sas...
ECML
2005
Springer
16 years 5 days ago
Natural Actor-Critic
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
Jan Peters, Sethu Vijayakumar, Stefan Schaal
SIGIR
2012
ACM
13 years 9 months ago
Parallelizing ListNet training using spark
As ever-larger training sets for learning to rank are created, scalability of learning has become increasingly important to achieving continuing improvements in ranking accuracy [...
Shilpa Shukla, Matthew Lease, Ambuj Tewari