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» Distributed Machine Learning: Scaling Up with Coarse-grained...
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NIPS
2008
13 years 9 months ago
Asynchronous Distributed Learning of Topic Models
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...
Arthur Asuncion, Padhraic Smyth, Max Welling
KDD
2007
ACM
132views Data Mining» more  KDD 2007»
14 years 8 months ago
A scalable modular convex solver for regularized risk minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
CONCURRENCY
1998
130views more  CONCURRENCY 1998»
13 years 8 months ago
JPVM: network parallel computing in Java
The JPVM library is a software system for explicit message-passing based distributed memory MIMD parallel programming in Java. The library supports an interface similar to the C a...
Adam Ferrari
ICS
2010
Tsinghua U.
13 years 11 months ago
Clustering performance data efficiently at massive scales
Existing supercomputers have hundreds of thousands of processor cores, and future systems may have hundreds of millions. Developers need detailed performance measurements to tune ...
Todd Gamblin, Bronis R. de Supinski, Martin Schulz...
IDEAL
2003
Springer
14 years 1 months ago
Detecting Distributed Denial of Service (DDoS) Attacks through Inductive Learning
As the complexity of Internet is scaled up, it is likely for the Internet resources to be exposed to Distributed Denial of Service (DDoS) flooding attacks on TCP-based Web servers....
Sanguk Noh, Cheolho Lee, Kyunghee Choi, Gihyun Jun...