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NIPS
1998
13 years 8 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
MICCAI
2005
Springer
14 years 8 months ago
Tissue Classification of Noisy MR Brain Images Using Constrained GMM
We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of G...
Amit Ruf, Hayit Greenspan, Jacob Goldberger
KDD
2002
ACM
118views Data Mining» more  KDD 2002»
14 years 8 months ago
SECRET: a scalable linear regression tree algorithm
Recently there has been an increasing interest in developing regression models for large datasets that are both accurate and easy to interpret. Regressors that have these properti...
Alin Dobra, Johannes Gehrke
PKDD
2010
Springer
184views Data Mining» more  PKDD 2010»
13 years 5 months ago
Shift-Invariant Grouped Multi-task Learning for Gaussian Processes
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Yuyang Wang, Roni Khardon, Pavlos Protopapas
ICPR
2002
IEEE
14 years 8 months ago
Fractional Component Analysis (FCA) for Mixed Signals
This paper proposes the fractional component analysis (FCA), whose goal is to decompose the observed signal into component signals and recover their fractions. The uniqueness of o...
Asanobu Kitamoto