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SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 11 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
COLING
2000
13 years 11 months ago
Learning Word Clusters from Data Types
The paper illustrates a linguistic knowledge acquisition model making use of data types, innite memory, and an inferential mechanism for inducing new information from known data. ...
Paolo Allegrini, Simonetta Montemagni, Vito Pirrel...
NIPS
1998
13 years 11 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
CIMCA
2005
IEEE
14 years 3 months ago
Fuzzy Inference Model for Learning from Experiences and Its Application to Robot Navigation
A fuzzy inference model for learning from experiences (FILE) is proposed. The model can learn from experience data obtained by trial-and-error of a task and it can stably learn fr...
Manabu Gouko, Yoshihiro Sugaya, Hirotomo Aso
KES
2004
Springer
14 years 3 months ago
Semi-supervised Learning from Unbalanced Labeled Data - An Improvement
Abstract. We present a possibly great improvement while performing semisupervised learning tasks from training data sets when only a small fraction of the data pairs is labeled. In...
Te Ming Huang, Vojislav Kecman