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FLAIRS
2003
15 years 8 months ago
Learning from Reinforcement and Advice Using Composite Reward Functions
1 Reinforcement learning has become a widely used methodology for creating intelligent agents in a wide range of applications. However, its performance deteriorates in tasks with s...
Vinay N. Papudesi, Manfred Huber
JMLR
2006
120views more  JMLR 2006»
15 years 6 months ago
Learning Parts-Based Representations of Data
Many perceptual models and theories hinge on treating objects as a collection of constituent parts. When applying these approaches to data, a fundamental problem arises: how can w...
David A. Ross, Richard S. Zemel
AIEDAM
1998
87views more  AIEDAM 1998»
15 years 6 months ago
Learning to set up numerical optimizations of engineering designs
Gradient-based numerical optimization of complex engineering designs offers the promise of rapidly producing better designs. However, such methods generally assume that the object...
Mark Schwabacher, Thomas Ellman, Haym Hirsh
AAAI
2010
15 years 4 months ago
Non-I.I.D. Multi-Instance Dimensionality Reduction by Learning a Maximum Bag Margin Subspace
Multi-instance learning, as other machine learning tasks, also suffers from the curse of dimensionality. Although dimensionality reduction methods have been investigated for many ...
Wei Ping, Ye Xu, Kexin Ren, Chi-Hung Chi, Shen Fur...
ICIP
2010
IEEE
15 years 4 months ago
Learning image similarities via Probabilistic Feature Matching
In this paper, we propose a novel image similarity learning approach based on Probabilistic Feature Matching (PFM). We consider the matching process as the bipartite graph matchin...
Ziming Zhang, Ze-Nian Li, Mark S. Drew