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ML
2002
ACM
220views Machine Learning» more  ML 2002»
14 years 9 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
TC
1998
14 years 9 months ago
Using System-Level Models to Evaluate I/O Subsystem Designs
—We describe a system-level simulation model and show that it enables accurate predictions of both I/O subsystem and overall system performance. In contrast, the conventional app...
Gregory R. Ganger, Yale N. Patt
SIGMETRICS
2002
ACM
128views Hardware» more  SIGMETRICS 2002»
14 years 9 months ago
High-density model for server allocation and placement
It is well known that optimal server placement is NP-hard. We present an approximate model for the case when both clients and servers are dense, and propose a simple server alloca...
Craig W. Cameron, Steven H. Low, David X. Wei
VLDB
2002
ACM
126views Database» more  VLDB 2002»
14 years 9 months ago
Exact Indexing of Dynamic Time Warping
The problem of indexing time series has attracted much interest. Most algorithms used to index time series utilize the Euclidean distance or some variation thereof. However, it has...
Eamonn J. Keogh
ML
2007
ACM
106views Machine Learning» more  ML 2007»
14 years 9 months ago
Surrogate maximization/minimization algorithms and extensions
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung