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» Algorithmic randomness of continuous functions
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ICASSP
2011
IEEE
14 years 1 months ago
Automatic speech recognition using Hidden Conditional Neural Fields
Hidden Conditional Random Fields(HCRF) is a very promising approach to model speech. However, because HCRF computes the score of a hypothesis by summing up linearly weighted featu...
Yasuhisa Fujii, Kazumasa Yamamoto, Seiichi Nakagaw...
ICPR
2004
IEEE
15 years 11 months ago
Reconstructing a Dynamic Surface from Video Sequences Using Graph Cuts in 4D Space-Time
This paper is concerned with the problem of dynamically reconstructing the 3D surface of an object undergoing non-rigid motion. The problem is cast as reconstructing a continuous ...
Narendra Ahuja, Ning Xu, Tianli Yu
JBI
2004
171views Bioinformatics» more  JBI 2004»
14 years 11 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...
JMLR
2012
13 years 8 days ago
Random Search for Hyper-Parameter Optimization
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
James Bergstra, Yoshua Bengio
GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
15 years 2 months ago
Benchmarking the (1+1)-ES with one-fifth success rule on the BBOB-2009 noisy testbed
The (1+1)-ES with one-fifth success rule is one of the first and simplest stochastic algorithm proposed for optimization on a continuous search space in a black-box scenario. In...
Anne Auger