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129
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AUSAI
2008
Springer
15 years 5 months ago
Revisiting Multiple-Instance Learning Via Embedded Instance Selection
Multiple-Instance Learning via Embedded Instance Selection (MILES) is a recently proposed multiple-instance (MI) classification algorithm that applies a single-instance base learne...
James R. Foulds, Eibe Frank
154
Voted
JMLR
2002
106views more  JMLR 2002»
15 years 3 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
ACL
2011
14 years 7 months ago
Learning to Win by Reading Manuals in a Monte-Carlo Framework
This paper presents a novel approach for leveraging automatically extracted textual knowledge to improve the performance of control applications such as games. Our ultimate goal i...
S. R. K. Branavan, David Silver, Regina Barzilay
AAAI
2012
13 years 6 months ago
Learning from Demonstration for Goal-Driven Autonomy
Goal-driven autonomy (GDA) is a conceptual model for creating an autonomous agent that monitors a set of expectations during plan execution, detects when discrepancies occur, buil...
Ben George Weber, Michael Mateas, Arnav Jhala
96
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ICSE
2003
IEEE-ACM
16 years 4 months ago
Quantifying the Value of Architecture Design Decisions: Lessons from the Field
This paper outlines experiences with using economic criteria to make architecture design decisions. It briefly describes the CBAM (Cost Benefit Analysis Method) framework applied ...
Mike Moore, Rick Kazman, Mark Klein, Jai Asundi