Sciweavers

492 search results - page 54 / 99
» A Failure to Learn from the Past
Sort
View
CORR
2012
Springer
170views Education» more  CORR 2012»
13 years 5 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson

Book
778views
16 years 8 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
AAMAS
2004
Springer
14 years 9 months ago
Autonomous Agents that Learn to Better Coordinate
A fundamental difficulty faced by groups of agents that work together is how to efficiently coordinate their efforts. This coordination problem is both ubiquitous and challenging,...
Andrew Garland, Richard Alterman
KDD
2008
ACM
159views Data Mining» more  KDD 2008»
15 years 10 months ago
Semi-supervised learning with data calibration for long-term time series forecasting
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
Haibin Cheng, Pang-Ning Tan
ATAL
2007
Springer
15 years 1 months ago
A reinforcement learning based distributed search algorithm for hierarchical peer-to-peer information retrieval systems
The dominant existing routing strategies employed in peerto-peer(P2P) based information retrieval(IR) systems are similarity-based approaches. In these approaches, agents depend o...
Haizheng Zhang, Victor R. Lesser