Sciweavers

143 search results - page 6 / 29
» On Using Machine Learning for Logic BIST
Sort
View
ICML
2009
IEEE
14 years 8 months ago
Deep transfer via second-order Markov logic
Standard inductive learning requires that training and test instances come from the same distribution. Transfer learning seeks to remove this restriction. In shallow transfer, tes...
Jesse Davis, Pedro Domingos
DEXAW
2007
IEEE
138views Database» more  DEXAW 2007»
14 years 1 months ago
Machine Learning for Question Answering from Tabular Data
Question Answering (QA) systems automatically answer natural language questions in a human-like manner. One of the practical approaches to open domain QA consists in extracting fa...
Mahboob Alam Khalid, Valentin Jijkoun, Maarten de ...
MLG
2007
Springer
14 years 1 months ago
Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, Jose Santos
JIIS
2000
120views more  JIIS 2000»
13 years 7 months ago
Machine Learning for Intelligent Processing of Printed Documents
Abstract. A paper document processing system is an information system component which transforms information on printed or handwritten documents into a computer-revisable form. In ...
Floriana Esposito, Donato Malerba, Francesca A. Li...
ICML
2007
IEEE
14 years 8 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney