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CVPR
2011
IEEE
15 years 1 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
135
Voted
SIGIR
2003
ACM
15 years 10 months ago
Modeling annotated data
We consider the problem of modeling annotated data—data with multiple types where the instance of one type (such as a caption) serves as a description of the other type (such as...
David M. Blei, Michael I. Jordan
AAAI
2008
15 years 7 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
SACRYPT
2004
Springer
143views Cryptology» more  SACRYPT 2004»
15 years 10 months ago
Blockwise Adversarial Model for On-line Ciphers and Symmetric Encryption Schemes
Abstract. This paper formalizes the security adversarial games for online symmetric cryptosystems in a unified framework for deterministic and probabilistic encryption schemes. On...
Pierre-Alain Fouque, Antoine Joux, Guillaume Poupa...
MICRO
2006
IEEE
159views Hardware» more  MICRO 2006»
15 years 4 months ago
MRF Reinforcer: A Probabilistic Element for Space Redundancy in Nanoscale Circuits
Shrinking devices to the nanoscale, increasing integration densities, and reducing of voltage levels down to the thermal limit, all conspire to produce faulty systems. Frequent oc...
Kundan Nepal, R. Iris Bahar, Joseph L. Mundy, Will...