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» Learning and Generalization with the Information Bottleneck
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IJCAI
2001
15 years 1 months ago
Adaptive Information Extraction from Text by Rule Induction and Generalisation
(LP)2 is a covering algorithm for adaptive Information Extraction from text (IE). It induces symbolic rules that insert SGML tags into texts by learning from examples found in a u...
Fabio Ciravegna
ICML
2005
IEEE
16 years 19 days ago
Learning strategies for story comprehension: a reinforcement learning approach
This paper describes the use of machine learning to improve the performance of natural language question answering systems. We present a model for improving story comprehension th...
Eugene Grois, David C. Wilkins
AAAI
2008
15 years 2 months ago
A Case Study on the Critical Role of Geometric Regularity in Machine Learning
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
Jason Gauci, Kenneth O. Stanley
BMCBI
2010
179views more  BMCBI 2010»
14 years 12 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
ICML
2007
IEEE
16 years 19 days ago
Robust multi-task learning with t-processes
Most current multi-task learning frameworks ignore the robustness issue, which means that the presence of "outlier" tasks may greatly reduce overall system performance. ...
Shipeng Yu, Volker Tresp, Kai Yu