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COLT
1999
Springer
13 years 12 months ago
Regret Bounds for Prediction Problems
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Geoffrey J. Gordon
CIKM
2010
Springer
13 years 6 months ago
Multi-view clustering with constraint propagation for learning with an incomplete mapping between views
Multi-view learning algorithms typically assume a complete bipartite mapping between the different views in order to exchange information during the learning process. However, ma...
Eric Eaton, Marie desJardins, Sara Jacob
SIAMCO
2010
147views more  SIAMCO 2010»
13 years 6 months ago
Anytime Reliable Transmission of Real-Valued Information through Digital Noisy Channels
Abstract. The problem of reliably transmitting a real-valued random vector through a digital noisy channel is relevant for the design of distributed estimation and control techniqu...
Giacomo Como, Fabio Fagnani, Sandro Zampieri
CVPR
2010
IEEE
14 years 3 months ago
Parametric Dimensionality Reduction by Unsupervised Regression
We introduce a parametric version (pDRUR) of the recently proposed Dimensionality Reduction by Unsupervised Regression algorithm. pDRUR alternately minimizes reconstruction error ...
Miguel Carreira-perpinan, Zhengdong Lu
IJRR
2008
139views more  IJRR 2008»
13 years 7 months ago
Learning to Control in Operational Space
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
Jan Peters, Stefan Schaal