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» Online Gradient Descent Learning Algorithms
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ICPR
2008
IEEE
14 years 8 months ago
Collaborative learning by boosting in distributed environments
In this paper we propose a new distributed learning method called distributed network boosting (DNB) algorithm for distributed applications. The learned hypotheses are exchanged b...
Shijun Wang, Changshui Zhang
NIPS
2001
13 years 8 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
CEAS
2006
Springer
13 years 11 months ago
Online Discriminative Spam Filter Training
We describe a very simple technique for discriminatively training a spam filter. Our results on the TREC Enron spam corpus would have been the best for the Ham at .1% measure, and...
Joshua Goodman, Wen-tau Yih
WWW
2010
ACM
14 years 2 months ago
Web-scale k-means clustering
We present two modifications to the popular k-means clustering algorithm to address the extreme requirements for latency, scalability, and sparsity encountered in user-facing web...
D. Sculley
CORR
2010
Springer
103views Education» more  CORR 2010»
13 years 7 months ago
On the Finite Time Convergence of Cyclic Coordinate Descent Methods
Cyclic coordinate descent is a classic optimization method that has witnessed a resurgence of interest in machine learning. Reasons for this include its simplicity, speed and stab...
Ankan Saha, Ambuj Tewari