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AI
2011
Springer
14 years 11 months ago
Learning qualitative models from numerical data
Qualitative models are often a useful abstraction of the physical world. Learning qualitative models from numerical data sible way to obtain such an abstraction. We present a new ...
Jure Zabkar, Martin Mozina, Ivan Bratko, Janez Dem...
200
Voted
ICCV
2011
IEEE
14 years 4 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 3 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 ...
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
15 years 9 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
CVPR
2004
IEEE
16 years 6 months ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...