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COLING
2008
15 years 1 months ago
Textual Demand Analysis: Detection of Users' Wants and Needs from Opinions
This paper tackles textual demand analysis, the task of capturing what people want or need, rather than identifying what they like or dislike, on which much conventional work has ...
Hiroshi Kanayama, Tetsuya Nasukawa
EMNLP
2010
14 years 9 months ago
Improved Fully Unsupervised Parsing with Zoomed Learning
We introduce a novel training algorithm for unsupervised grammar induction, called Zoomed Learning. Given a training set T and a test set S, the goal of our algorithm is to identi...
Roi Reichart, Ari Rappoport
FLAIRS
2007
15 years 2 months ago
Context-Sensitive MTL Networks for Machine Lifelong Learning
Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer that uses a single output neural network and additional contextual inputs for le...
Daniel L. Silver, Ryan Poirier
METMBS
2003
255views Mathematics» more  METMBS 2003»
15 years 1 months ago
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery
Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...
CORR
2011
Springer
172views Education» more  CORR 2011»
14 years 6 months ago
Improving Strategies via SMT Solving
We consider the problem of computing numerical invariants of programs by abstract interpretation. Our method eschews two traditional sources of imprecision: (i) the use of widenin...
Thomas Martin Gawlitza, David Monniaux