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ACL
2006
15 years 1 months ago
An End-to-End Discriminative Approach to Machine Translation
We present a perceptron-style discriminative approach to machine translation in which large feature sets can be exploited. Unlike discriminative reranking approaches, our system c...
Percy Liang, Alexandre Bouchard-Côté,...
110
Voted
ICML
2004
IEEE
16 years 1 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...
113
Voted
PAKDD
2011
ACM
245views Data Mining» more  PAKDD 2011»
14 years 3 months ago
Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy M. Hospedales, Shaogang Gong, Tao Xiang
ICML
2009
IEEE
16 years 1 months ago
Trajectory prediction: learning to map situations to robot trajectories
Trajectory planning and optimization is a fundamental problem in articulated robotics. Algorithms used typically for this problem compute optimal trajectories from scratch in a ne...
Nikolay Jetchev, Marc Toussaint
NIPS
2007
15 years 1 months ago
Multi-Task Learning via Conic Programming
When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task learning (MTL) and...
Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, ...