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» Learning and Inference with Constraints
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SDM
2004
SIAM
142views Data Mining» more  SDM 2004»
15 years 7 months ago
Learning to Read Between the Lines: The Aspect Bernoulli Model
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...
Ata Kabán, Ella Bingham, T. Hirsimäki
ACL
2010
15 years 4 months ago
Learning Common Grammar from Multilingual Corpus
We propose a corpus-based probabilistic framework to extract hidden common syntax across languages from non-parallel multilingual corpora in an unsupervised fashion. For this purp...
Tomoharu Iwata, Daichi Mochihashi, Hiroshi Sawada
DAC
2006
ACM
16 years 14 days ago
Mining global constraints for improving bounded sequential equivalence checking
In this paper, we propose a novel technique on mining relationships in a sequential circuit to discover global constraints. In contrast to the traditional learning methods, our mi...
Weixin Wu, Michael S. Hsiao
FLAIRS
2007
15 years 8 months ago
Search Ordering Heuristics for Restarts-Based Constraint Solving
Constraint Satisfaction Problems are ubiquitous in Artificial Intelligence. Over the past decade significant advances have been made in terms of the size of problem instance tha...
Margarita Razgon, Barry O'Sullivan, Gregory M. Pro...
AIMSA
2008
Springer
15 years 8 months ago
A Hybrid Approach to Distributed Constraint Satisfaction
We present a hybrid approach to Distributed Constraint Satisfaction which combines incomplete, fast, penalty-based local search with complete, slower systematic search. Thus, we pr...
David Lee, Inés Arana, Hatem Ahriz, Kit-Yin...