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» Approximation Lasso Methods for Language Modeling
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CORR
2012
Springer
170views Education» more  CORR 2012»
12 years 3 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
EMNLP
2006
13 years 9 months ago
Relevance Feedback Models for Recommendation
We extended language modeling approaches in information retrieval (IR) to combine collaborative filtering (CF) and content-based filtering (CBF). Our approach is based on the anal...
Masao Utiyama, Mikio Yamamoto
ATAL
1997
Springer
14 years 17 hour ago
Approximate Reasoning about Combined Knowledge
Abstract. Just as cooperation in multi-agent systems is a central issue for solving complex tasks, so too is the ability for an intelligent agent to reason about combined knowledge...
Frédéric Koriche
ACL
2009
13 years 5 months ago
Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Yoshimasa Tsuruoka, Jun-ichi Tsujii, Sophia Anania...
FMSD
2006
103views more  FMSD 2006»
13 years 7 months ago
Compositional SCC Analysis for Language Emptiness
We propose a refinement approach to language emptiness, which is based on the enumeration and the successive refinements of SCCs on over-approximations of the exact system. Our alg...
Chao Wang, Roderick Bloem, Gary D. Hachtel, Kavita...