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» Randomness, Stochasticity and Approximations
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FOCS
2003
IEEE
14 years 2 months ago
Switch Scheduling via Randomized Edge Coloring
The essence of an Internet router is an n ¡ n switch which routes packets from input to output ports. Such a switch can be viewed as a bipartite graph with the input and output p...
Gagan Aggarwal, Rajeev Motwani, Devavrat Shah, An ...
CP
2006
Springer
14 years 29 days ago
Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
ACL
2008
13 years 10 months ago
Efficient, Feature-based, Conditional Random Field Parsing
Discriminative feature-based methods are widely used in natural language processing, but sentence parsing is still dominated by generative methods. While prior feature-based dynam...
Jenny Rose Finkel, Alex Kleeman, Christopher D. Ma...
ICDAR
2009
IEEE
13 years 7 months ago
Unconstrained Handwritten Document Layout Extraction Using 2D Conditional Random Fields
The paper describes a new approach using a Conditional Random Fields (CRFs) to extract physical and logical layouts in unconstrained handwritten letters such as those sent by indi...
Florent Montreuil, Emmanuele Grosicki, Laurent Heu...
JMLR
2010
145views more  JMLR 2010»
13 years 4 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever