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» Approximate algorithms for neural-Bayesian approaches
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ATVA
2008
Springer
99views Hardware» more  ATVA 2008»
15 years 8 months ago
Model Checking Recursive Programs with Exact Predicate Abstraction
e Abstraction Arie Gurfinkel1 , Ou Wei2 , and Marsha Chechik2 1 Software Engineering Institute, Carnegie Mellon University 2 Department of Computer Science, University of Toronto A...
Arie Gurfinkel, Ou Wei, Marsha Chechik
152
Voted
NIPS
2001
15 years 7 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
195
Voted
PAMI
2010
168views more  PAMI 2010»
15 years 4 months ago
Surface-from-Gradients without Discrete Integrability Enforcement: A Gaussian Kernel Approach
—Representative surface reconstruction algorithms taking a gradient field as input enforces the integrability constraint in a discrete manner. While enforcing integrability allo...
Heung-Sun Ng, Tai-Pang Wu, Chi-Keung Tang
KDD
2008
ACM
178views Data Mining» more  KDD 2008»
16 years 6 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
183
Voted
ICCV
2011
IEEE
14 years 6 months ago
N-best maximal decoders for part models
We describe a method for generating N-best configurations from part-based models, ensuring that they do not overlap according to some user-provided definition of overlap. We ext...
Dennis Park, Deva Ramanan