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JMLR
2010
118views more  JMLR 2010»
11 years 8 months ago
Dirichlet Process Mixtures of Generalized Linear Models
We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLMs), a new method of nonparametric regression that accommodates continuous and categorical inputs, models ...
Lauren Hannah, David M. Blei, Warren B. Powell
CSSC
2008
84views more  CSSC 2008»
12 years 1 months ago
Nonparametric Regression as an Example of Model Choice
Nonparametric regression can be considered as a problem of model choice. In this paper we present the results of a simulation study in which several nonparametric regression techn...
Laurie Davies, Ursula Gather, Henrike Weinert
NIPS
2007
12 years 3 months ago
SpAM: Sparse Additive Models
We present a new class of models for high-dimensional nonparametric regression and classiļ¬cation called sparse additive models (SpAM). Our methods combine ideas from sparse line...
Pradeep D. Ravikumar, Han Liu, John D. Lafferty, L...
NIPS
2008
12 years 3 months ago
Bayesian Kernel Shaping for Learning Control
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakum...
KDD
2000
ACM
162views Data Mining» more  KDD 2000»
12 years 5 months ago
Data Mining from Functional Brain Images
Recent advances in functional brain imaging enable identication of active areas of a brain performing a certain function. Induction of logical formulas describing relations betwee...
Mitsuru Kakimoto, Chie Morita, Yoshiaki Kikuchi, H...
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