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ICTAI
2009
IEEE
16 years 16 days 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 8 months 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»
15 years 5 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
15 years 5 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
16 years 2 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