ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
We describe a class of causal, discrete latent variable models called Multiple Multiplicative Factor models (MMFs). A data vector is represented in the latent space as a vector of...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
We propose a simple, novel and yet effective method for building and testing decision trees that minimizes the sum of the misclassification and test costs. More specifically, we f...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Abstraction in Reinforcement Learning via Clustering Shie Mannor shie@mit.edu Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA ...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
The assumptions behind linear classifiers for categorical data are examined and reformulated in the context of the multinomial manifold, the simplex of multinomial models furnishe...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Boosting is a popular approach for building accurate classifiers. Despite the initial popular belief, boosting algorithms do exhibit overfitting and are sensitive to label noise. ...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Motivated by the interest in relational reinforcement learning, we introduce a novel relational Bellman update operator called ReBel. It employs a constraint logic programming lan...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
The goal of feature induction is to automatically create nonlinear combinations of existing features as additional input features to improve classification accuracy. Typically, no...