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ICTAI
2009
IEEE
15 years 4 months ago
EBLearn: Open-Source Energy-Based Learning in C++
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
Pierre Sermanet, Koray Kavukcuoglu, Yann LeCun
CVPR
2008
IEEE
16 years 3 days ago
Conditional density learning via regression with application to deformable shape segmentation
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
FOCM
2006
50views more  FOCM 2006»
14 years 10 months ago
Online Learning Algorithms
In this paper, we study an online learning algorithm in Reproducing Kernel Hilbert Spaces (RKHS) and general Hilbert spaces. We present a general form of the stochastic gradient m...
Steve Smale, Yuan Yao
PAA
2008
14 years 10 months ago
A sparse Bayesian approach for joint feature selection and classifier learning
Abstract In this paper we present a new method for Joint Feature Selection and Classifier Learning (JFSCL) using a sparse Bayesian approach. These tasks are performed by optimizing...
Àgata Lapedriza, Santi Seguí, David ...
ALT
2001
Springer
15 years 7 months ago
Learning How to Separate
The main question addressed in the present work is how to find effectively a recursive function separating two sets drawn arbitrarily from a given collection of disjoint sets. I...
Sanjay Jain, Frank Stephan