Sciweavers

ICML
2003
IEEE
14 years 5 months ago
Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries
Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of ...
Jeremy Kubica, Andrew W. Moore, David Cohn, Jeff G...
ICML
2003
IEEE
14 years 5 months ago
Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers
We show that a classifier based on Gaussian mixture models (GMM) can be trained discriminatively to improve accuracy. We describe a training procedure based on the extended Baum-W...
Aldebaro Klautau, Nikola Jevtic, Alon Orlitsky
ICML
2003
IEEE
14 years 5 months ago
Unsupervised Learning with Permuted Data
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
Sergey Kirshner, Sridevi Parise, Padhraic Smyth
ICML
2003
IEEE
14 years 5 months ago
Classification of Text Documents Based on Minimum System Entropy
Raghu Krishnapuram, Krishna Prasad Chitrapura, Sac...
ICML
2003
IEEE
14 years 5 months ago
Visual Learning by Evolutionary Feature Synthesis
Krzysztof Krawiec, Bir Bhanu
ICML
2003
IEEE
14 years 5 months ago
Informative Discriminant Analysis
Samuel Kaski, Jaakko Peltonen
ICML
2003
IEEE
14 years 5 months ago
Marginalized Kernels Between Labeled Graphs
A new kernel function between two labeled graphs is presented. Feature vectors are defined as the counts of label paths produced by random walks on graphs. The kernel computation ...
Hisashi Kashima, Koji Tsuda, Akihiro Inokuchi
ICML
2003
IEEE
14 years 5 months ago
Representational Issues in Meta-Learning
To address the problem of algorithm selection for the classification task, we equip a relational case base with new similarity measures that are able to cope with multirelational ...
Alexandros Kalousis, Melanie Hilario
ICML
2003
IEEE
14 years 5 months ago
Exploration in Metric State Spaces
We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
Sham Kakade, Michael J. Kearns, John Langford