158 search results - page 6 / 32 » A Dynamic Adaptation of AD-trees for Efficient Machine Learn... |
NEUROSCIENCE
2001
Springer
13 years 12 months ago
2001
Springer
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
COLT
2010
Springer
13 years 5 months ago
2010
Springer
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
ALGORITHMICA
2010
13 years 7 months ago
2010
We divide a string into k segments, each with only one sort of symbols, so as to minimize the total number of exceptions. Motivations come from machine learning and data mining. F...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...