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» Approximate algorithms for neural-Bayesian approaches
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ICASSP
2009
IEEE
15 years 4 months ago
Maximizing global entropy reduction for active learning in speech recognition
We propose a new active learning algorithm to address the problem of selecting a limited subset of utterances for transcribing from a large amount of unlabeled utterances so that ...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
NIPS
2008
14 years 11 months ago
Improved Moves for Truncated Convex Models
We consider the problem of obtaining the approximate maximum a posteriori estimate of a discrete random field characterized by pairwise potentials that form a truncated convex mod...
M. Pawan Kumar, Philip H. S. Torr
FOCS
2007
IEEE
15 years 4 months ago
Adaptive Simulated Annealing: A Near-optimal Connection between Sampling and Counting
We present a near-optimal reduction from approximately counting the cardinality of a discrete set to approximately sampling elements of the set. An important application of our wo...
Daniel Stefankovic, Santosh Vempala, Eric Vigoda
SODA
2010
ACM
197views Algorithms» more  SODA 2010»
15 years 7 months ago
Quasirandom Load Balancing
We propose a simple distributed algorithm for balancing indivisible tokens on graphs. The algorithm is completely deterministic, though it tries to imitate (and enhance) a random ...
Tobias Friedrich, Martin Gairing, Thomas Sauerwald
TIP
1998
109views more  TIP 1998»
14 years 9 months ago
Optimum design of chamfer distance transforms
—The distance transform has found many applications in image analysis. Chamfer distance transforms are a class of discrete algorithms that offer a good approximation to the desir...
Muhammad Akmal Butt, Petros Maragos