315 search results - page 7 / 63 » Structural Learning from Iconic Representations |
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
IDA
2003
Springer
14 years 20 days ago
2003
Springer
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
AI
1999
Springer
13 years 7 months ago
1999
Springer
Reasoning about the physical world is a central human cognitive activity. One aspect of such reasoning is the inference of function from the structure of the artifacts one encount...
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...