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NIPS
1997
13 years 11 months ago
Relative Loss Bounds for Multidimensional Regression Problems
We study on-line generalized linear regression with multidimensional outputs, i.e., neural networks with multiple output nodes but no hidden nodes. We allow at the final layer tra...
Jyrki Kivinen, Manfred K. Warmuth
EOR
2008
99views more  EOR 2008»
13 years 10 months ago
Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions
We present a new method, called UTAGMS , for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. ...
Salvatore Greco, Vincent Mousseau, Roman Slowinski
BMCBI
2011
13 years 1 months ago
A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...
Alfredo A. Kalaitzis, Neil D. Lawrence
MLCW
2005
Springer
14 years 3 months ago
Estimating Predictive Variances with Kernel Ridge Regression
In many regression tasks, in addition to an accurate estimate of the conditional mean of the target distribution, an indication of the predictive uncertainty is also required. Ther...
Gavin C. Cawley, Nicola L. C. Talbot, Olivier Chap...
AAAI
1994
13 years 11 months ago
Learning Explanation-Based Search Control Rules for Partial Order Planning
This paper presents snlp+ebl, the first implementation of explanation based learning techniques for a partial order planner. We describe the basic learning framework of snlp+ebl, ...
Suresh Katukam, Subbarao Kambhampati