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NIPS
2001
14 years 11 months ago
A Parallel Mixture of SVMs for Very Large Scale Problems
Support Vector Machines (SVMs) are currently the state-of-the-art models for many classication problems but they suer from the complexity of their training algorithm which is at l...
Ronan Collobert, Samy Bengio, Yoshua Bengio
SEAL
2010
Springer
14 years 7 months ago
Dominance-Based Pareto-Surrogate for Multi-Objective Optimization
Abstract. Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Paret...
Ilya Loshchilov, Marc Schoenauer, Michèle S...
ECML
2006
Springer
15 years 1 months ago
Constant Rate Approximate Maximum Margin Algorithms
We present a new class of perceptron-like algorithms with margin in which the "effective" learning rate, defined as the ratio of the learning rate to the length of the we...
Petroula Tsampouka, John Shawe-Taylor
ICCD
1999
IEEE
88views Hardware» more  ICCD 1999»
15 years 2 months ago
TriMedia CPU64 Application Development Environment
The architecture of the TriMedia CPU64 is based on the TM1000 DSPCPU. The original VLIW architecture has been extended with the concepts of vector processing and superoperations. ...
Evert-Jan D. Pol, Bas Aarts, Jos T. J. van Eijndho...
FOCS
2010
IEEE
14 years 8 months ago
Learning Convex Concepts from Gaussian Distributions with PCA
We present a new algorithm for learning a convex set in n-dimensional space given labeled examples drawn from any Gaussian distribution. The complexity of the algorithm is bounded ...
Santosh Vempala