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NIPS
2008
13 years 8 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
TIP
2010
136views more  TIP 2010»
13 years 5 months ago
Wavelet Steerability and the Higher-Order Riesz Transform
Abstract— Our main goal in this paper is to set the foundations of a general continuous-domain framework for designing steerable, reversible signal transformations (a.k.a. frames...
Michael Unser, Dimitri Van De Ville
ML
2010
ACM
163views Machine Learning» more  ML 2010»
13 years 2 months ago
Classification with guaranteed probability of error
We introduce a general-purpose learning machine that we call the Guaranteed Error Machine, or GEM, and two learning algorithms, a real GEM algorithm and an ideal GEM algorithm. Th...
Marco C. Campi
CEC
2010
IEEE
13 years 8 months ago
Generating a novel sort algorithm using Reinforcement Programming
Abstract-- Reinforcement Programming (RP) is a new approach to automatically generating algorithms, that uses reinforcement learning techniques. This paper describes the RP approac...
Spencer K. White, Tony R. Martinez, George L. Rudo...
EMSOFT
2004
Springer
14 years 24 days ago
Approximation of the worst-case execution time using structural analysis
We present a technique to approximate the worst-case execution time that combines structural analysis with a loop-bounding algorithm based on local induction variable analysis. St...
Matteo Corti, Thomas R. Gross