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ICCV
2011
IEEE
12 years 7 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
ECAL
2005
Springer
14 years 1 months ago
On the Mean Convergence Time of Multi-parent Genetic Algorithms Without Selection
This paper investigates genetic drift in multi-parent genetic algorithms (MPGAs). An exact model based on Markov chains is proposed to formulate the variation of gene frequency. Th...
Chuan-Kang Ting
NIPS
2008
13 years 9 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
ACSD
2010
IEEE
220views Hardware» more  ACSD 2010»
13 years 5 months ago
Towards Performance Evaluation of Mobile Ad Hoc Network Protocols
We present a formal framework to evaluate stochastic properties of MANET protocols. It captures the interplay between stochastic behavior of protocols deployed at different network...
Fatemeh Ghassemi, Ali Movaghar, Wan Fokkink
FORTE
2004
13 years 9 months ago
Symbolic Performance and Dependability Evaluation with the Tool CASPA
This paper describes the tool CASPA, a new performance evaluation tool which is based on a Markovian stochastic process algebra. CASPA uses multi-terminal binary decision diagrams ...
Matthias Kuntz, Markus Siegle, Edith Werner