363 search results - page 48 / 73 » GraphLab: A New Framework for Parallel Machine Learning |
ML
2008
ACM
13 years 8 months ago
2008
ACM
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
NIPS
2008
13 years 10 months ago
2008
Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
HPDC
2008
IEEE
14 years 3 months ago
2008
IEEE
Active storage clouds are an attractive platform for executing large data intensive workloads found in many fields of science. However, active storage presents new system managem...
COLT
1999
Springer
14 years 1 months ago
1999
Springer
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
ICML
2010
IEEE
13 years 9 months ago
2010
IEEE
Optimization problems with a nuclear norm regularization, such as e.g. low norm matrix factorizations, have seen many applications recently. We propose a new approximation algorit...