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ATAL
2010
Springer
13 years 9 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
PR
2006
164views more  PR 2006»
13 years 8 months ago
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
Hong Chang, Dit-Yan Yeung
CORR
2007
Springer
111views Education» more  CORR 2007»
13 years 8 months ago
Capacity of Sparse Multipath Channels in the Ultra-Wideband Regime
—This paper studies the ergodic capacity of time- and frequency-selective multipath fading channels in the ultrawideband (UWB) regime when training signals are used for channel e...
Vasanthan Raghavan, Gautham Hariharan, Akbar M. Sa...
CVPR
2006
IEEE
14 years 10 months ago
Unsupervised Discovery of Action Classes
In this paper we consider the problem of describing the action being performed by human figures in still images. We will attack this problem using an unsupervised learning approac...
Greg Mori, Hao Jiang, Mark S. Drew, Yang Wang 0003...
ICML
2009
IEEE
14 years 9 months ago
Robust bounds for classification via selective sampling
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
Nicolò Cesa-Bianchi, Claudio Gentile, Franc...