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AAAI
2010
13 years 11 months ago
Bayesian Matrix Factorization with Side Information and Dirichlet Process Mixtures
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
Ian Porteous, Arthur Asuncion, Max Welling
DICTA
2008
13 years 11 months ago
Exploiting Part-Based Models and Edge Boundaries for Object Detection
This paper explores how to exploit shape information to perform object class recognition. We use a sparse partbased model to describe object categories defined by shape. The spars...
Josephine Sullivan, Oscar M. Danielsson, Stefan Ca...
JSSPP
2005
Springer
14 years 3 months ago
ScoPred-Scalable User-Directed Performance Prediction Using Complexity Modeling and Historical Data
Using historical information to predict future runs of parallel jobs has shown to be valuable in job scheduling. Trends toward more flexible jobscheduling techniques such as adapt...
Benjamin J. Lafreniere, Angela C. Sodan
ACCV
2010
Springer
13 years 4 months ago
Estimating Meteorological Visibility Using Cameras: A Probabilistic Model-Driven Approach
Estimating the atmospheric or meteorological visibility distance is very important for air and ground transport safety, as well as for air quality. However, there is no holistic ap...
Nicolas Hautière, Raouf Babari, Eric Dumont...
IJON
2010
109views more  IJON 2010»
13 years 4 months ago
Variational inference for Student-t MLP models
This paper presents a novel methodology to infer parameters of probabilistic models whose output noise is a Student-t distribution. The method is an extension of earlier work for ...
Hang T. Nguyen, Ian T. Nabney