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KDD
2007
ACM
132views Data Mining» more  KDD 2007»
14 years 7 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...
ICDM
2007
IEEE
137views Data Mining» more  ICDM 2007»
14 years 1 months ago
Locally Constrained Support Vector Clustering
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...
Dragomir Yankov, Eamonn J. Keogh, Kin Fai Kan
ICFP
2010
ACM
13 years 8 months ago
Regular, shape-polymorphic, parallel arrays in Haskell
We present a novel approach to regular, multi-dimensional arrays in Haskell. The main highlights of our approach are that it (1) is purely functional, (2) supports reuse through s...
Gabriele Keller, Manuel M. T. Chakravarty, Roman L...
JMLR
2010
135views more  JMLR 2010»
13 years 5 months ago
Bundle Methods 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 differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
ICLP
1995
Springer
13 years 10 months ago
A Method for Implementing Equational Theories as Logic Programs
Equational theories underly many elds of computing, including functional programming, symbolic algebra, theorem proving, term rewriting and constraint solving. In this paper we sh...
Mantis H. M. Cheng, Douglas Stott Parker Jr., Maar...