Sciweavers

38 search results - page 3 / 8
» Kernel Regression with Order Preferences
Sort
View
CORR
2012
Springer
214views Education» more  CORR 2012»
12 years 4 months ago
Stochastic Low-Rank Kernel Learning for Regression
We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic ...
Pierre Machart, Thomas Peel, Liva Ralaivola, Sandr...
ESANN
2003
13 years 10 months ago
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression
In this paper we extend a form of kernel ridge regression for data characterised by a heteroscedastic noise process (introduced in Foxall et al. [1]) in order to provide approxima...
Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Fo...
AAAI
2007
13 years 11 months ago
A Randomized String Kernel and Its Application to RNA Interference
String kernels directly model sequence similarities without the necessity of extracting numerical features in a vector space. Since they better capture complex traits in the seque...
Shibin Qiu, Terran Lane, Ljubomir J. Buturovic
ECWEB
2009
Springer
204views ECommerce» more  ECWEB 2009»
14 years 3 months ago
Computational Complexity Reduction for Factorization-Based Collaborative Filtering Algorithms
Abstract. Alternating least squares (ALS) is a powerful matrix factorization (MF) algorithm for both implicit and explicit feedback based recommender systems. We show that by using...
István Pilászy, Domonkos Tikk
WSOM
2009
Springer
14 years 3 months ago
Towards Semi-supervised Manifold Learning: UKR with Structural Hints
We explore generic mechanisms to introduce structural hints into the method of Unsupervised Kernel Regression (UKR) in order to learn representations of data sequences in a semi-su...
Jan Steffen, Stefan Klanke, Sethu Vijayakumar, Hel...