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» Sequential Inductive Learning
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AAAI
2008
15 years 3 months ago
Active Learning for Pipeline Models
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
Dan Roth, Kevin Small
101
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CHI
2009
ACM
16 years 1 months ago
Learning to predict information needs: context-aware display as a cognitive aid and an assessment tool
We discuss the problem of assessing and aiding user performance in dynamic tasks that require rapid selection among multiple information sources. Motivated by research in human se...
Bradley C. Love, Matt Jones, Marc T. Tomlinson, Mi...
102
Voted
ICML
2009
IEEE
16 years 1 months ago
Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties
We describe an algorithm for constructing a set of acyclic conjunctive relational features by combining smaller conjunctive blocks. Unlike traditional level-wise approaches which ...
Filip Zelezný, Ondrej Kuzelka
86
Voted
ICDM
2002
IEEE
70views Data Mining» more  ICDM 2002»
15 years 5 months ago
Progressive Modeling
Presently, inductive learning is still performed in a frustrating batch process. The user has little interaction with the system and no control over the final accuracy and traini...
Wei Fan, Haixun Wang, Philip S. Yu, Shaw-hwa Lo, S...
109
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COLING
2010
14 years 7 months ago
A Learnable Constraint-based Grammar Formalism
Lexicalized Well-Founded Grammar (LWFG) is a recently developed syntacticsemantic grammar formalism for deep language understanding, which balances expressiveness with provable le...
Smaranda Muresan