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CHI
2011
ACM
14 years 1 months ago
Apolo: making sense of large network data by combining rich user interaction and machine learning
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
129
Voted
AAIP
2009
14 years 10 months ago
Incremental Learning in Inductive Programming
Inductive programming systems characteristically exhibit an exponential explosion in search time as one increases the size of the programs to be generated. As a way of overcoming ...
Robert Henderson
ALT
2000
Springer
15 years 6 months ago
Learning Recursive Concepts with Anomalies
This paper provides a systematic study of inductive inference of indexable concept classes in learning scenarios in which the learner is successful if its final hypothesis describ...
Gunter Grieser, Steffen Lange, Thomas Zeugmann
98
Voted
ICML
2006
IEEE
15 years 10 months ago
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
BMCBI
2010
125views more  BMCBI 2010»
14 years 9 months ago
Active machine learning for transmembrane helix prediction
Background: About 30% of genes code for membrane proteins, which are involved in a wide variety of crucial biological functions. Despite their importance, experimentally determine...
Hatice U. Osmanbeyoglu, Jessica A. Wehner, Jaime G...