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97
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ICCV
2005
IEEE
15 years 8 months ago
Learning Models for Predicting Recognition Performance
This paper addresses one of the fundamental problems encountered in performance prediction for object recognition. In particular we address the problems related to estimation of s...
Rong Wang, Bir Bhanu
119
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ATAL
2009
Springer
15 years 9 months ago
An empirical analysis of value function-based and policy search reinforcement learning
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
Shivaram Kalyanakrishnan, Peter Stone
172
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AI
2002
Springer
15 years 2 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
121
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WWW
2008
ACM
16 years 3 months ago
Enhanced hierarchical classification via isotonic smoothing
Hierarchical topic taxonomies have proliferated on the World Wide Web [5, 18], and exploiting the output space decompositions they induce in automated classification systems is an...
Kunal Punera, Joydeep Ghosh
132
Voted
TIP
2010
147views more  TIP 2010»
14 years 9 months ago
Deform PF-MT: Particle Filter With Mode Tracker for Tracking Nonaffine Contour Deformations
We propose algorithms for tracking the boundary contour of a deforming object from an image sequence, when the nonaffine (local) deformation over consecutive frames is large and th...
Namrata Vaswani, Yogesh Rathi, Anthony J. Yezzi, A...