ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
Many collective labeling tasks require inference on graphical models where the clique potentials depend only on the number of nodes that get a particular label. We design efficien...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
A plausible representation of relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network which is topologically r...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
Although each iteration of the popular kMeans clustering heuristic scales well to larger problem sizes, it often requires an unacceptably-high number of iterations to converge to ...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
We1 present a new actor-critic learning model in which a Bayesian class of non-parametric critics, using Gaussian process temporal difference learning is used. Such critics model ...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
The UCT algorithm learns a value function online using sample-based search. The TD() algorithm can learn a value function offline for the on-policy distribution. We consider three...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
Intuitively, learning should be easier when the data points lie on a low-dimensional submanifold of the input space. Recently there has been a growing interest in algorithms that ...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
We combine linear discriminant analysis (LDA) and K-means clustering into a coherent framework to adaptively select the most discriminative subspace. We use K-means clustering to ...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
Markov decision processes are an effective tool in modeling decision-making in uncertain dynamic environments. Since the parameters of these models are typically estimated from da...