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ICASSP
2008
IEEE
14 years 1 months ago
Nested support vector machines
The one-class and cost-sensitive support vector machines (SVMs) are state-of-the-art machine learning methods for estimating density level sets and solving weighted classificatio...
Gyemin Lee, Clayton Scott
ATAL
2008
Springer
13 years 8 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
JMLR
2012
11 years 9 months ago
Multi Kernel Learning with Online-Batch Optimization
In recent years there has been a lot of interest in designing principled classification algorithms over multiple cues, based on the intuitive notion that using more features shou...
Francesco Orabona, Jie Luo, Barbara Caputo
ESANN
2001
13 years 8 months ago
A divide-and-conquer learning architecture for predicting unknown motion
Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
Patrice Wira, Jean-Philippe Urban, Julien Gresser
ECCV
2004
Springer
14 years 8 months ago
Synthesizing Dynamic Texture with Closed-Loop Linear Dynamic System
Dynamic texture can be defined as a temporally continuous and infinitely varying stream of images that exhibit certain temporal statistics. Linear dynamic system (LDS) represented ...
Lu Yuan, Fang Wen, Ce Liu, Heung-Yeung Shum