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CVPR
2011
IEEE
15 years 2 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...
JMLR
2010
136views more  JMLR 2010»
15 years 1 months ago
Predicting the functions of proteins in Protein-Protein Interaction networks from global information
In this work we present a novel approach to predict the function of proteins in protein-protein interaction (PPI) networks. We classify existing approaches into inductive and tran...
Hossein Rahmani, Hendrik Blockeel, Andreas Bender
AAAI
1997
15 years 7 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer
BNCOD
1997
76views Database» more  BNCOD 1997»
15 years 7 months ago
Query Evaluation in CROQUE - Calculus and Algebra Coincide
With the substantial change of declarative query languages from plain SQL to the so-called \object SQLs", in particular OQL, there has surprisingly been not much change in the...
Torsten Grust, Joachim Kröger, Dieter Gluche,...
ECAI
2010
Springer
15 years 7 months ago
On Finding Compromise Solutions in Multiobjective Markov Decision Processes
A Markov Decision Process (MDP) is a general model for solving planning problems under uncertainty. It has been extended to multiobjective MDP to address multicriteria or multiagen...
Patrice Perny, Paul Weng