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ICML
2003
IEEE
16 years 8 months ago
Exploration in Metric State Spaces
We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
Sham Kakade, Michael J. Kearns, John Langford
STOC
2004
ACM
131views Algorithms» more  STOC 2004»
16 years 7 months ago
(Almost) tight bounds and existence theorems for confluent flows
A flow is said to be confluent if at any node all the flow leaves along a single edge. Given a directed graph G with k sinks and non-negative demands on all the nodes of G, we con...
Jiangzhuo Chen, Robert D. Kleinberg, Lászl&...
ICML
2009
IEEE
16 years 1 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider
ICASSP
2009
IEEE
16 years 1 months ago
Reconstruction of isometrically deformable flat surfaces in 3D from multiple camera images
This paper deals with the reconstruction of smooth, flexible, isometrically embedded flat surfaces in 3D, such as a sheet of paper or a flag waving in the wind, from a set of 2...
Ricardo Ferreira, João Xavier, João ...
ICASSP
2008
IEEE
16 years 1 months ago
Multi-source DOA estimation in a reverberant room
In a reverberant scenario, phase transformed weighted algorithms are more robust than Maximum Likelihood (ML) because of the insufficiency of the data model to incorporate reverb...
Andreas M. Ali, Ralph E. Hudson, Kung Yao