ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
The proliferation of text documents on the web as well as within institutions necessitates their convenient organization to enable efficient retrieval of information. Although tex...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In the information regularization framework by Corduneanu and Jaakkola (2005), the distributions of labels are propagated on a hypergraph for semi-supervised learning. The learnin...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Sensorimotor data from many interesting physical interactions comprises discontinuities. While existing locally weighted learning approaches aim at learning smooth functions, we p...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Linear discriminant analysis (LDA) has been an active topic of research during the last century. However, the existing algorithms have several limitations when applied to visual d...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In this paper we consider sampling based fitted value iteration for discounted, large (possibly infinite) state space, finite action Markovian Decision Problems where only a gener...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Learning the structure of graphical models is an important task, but one of considerable difficulty when latent variables are involved. Because conditional independences using hid...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In this paper, we present a new interpretation of AdaBoost.ECC and AdaBoost.OC. We show that AdaBoost.ECC performs stage-wise functional gradient descent on a cost function, defin...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
For Hidden Markov Models (HMMs) with fully connected transition models, the three fundamental problems of evaluating the likelihood of an observation sequence, estimating an optim...