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145
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ICML
2005
IEEE
16 years 4 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
140
Voted
ICML
2010
IEEE
15 years 4 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
124
Voted
SDM
2008
SIAM
197views Data Mining» more  SDM 2008»
15 years 5 months ago
A general framework for estimating similarity of datasets and decision trees: exploring semantic similarity of decision trees
Decision trees are among the most popular pattern types in data mining due to their intuitive representation. However, little attention has been given on the definition of measure...
Irene Ntoutsi, Alexandros Kalousis, Yannis Theodor...
148
Voted
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
16 years 4 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
123
Voted
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
16 years 4 months ago
Sequential cost-sensitive decision making with reinforcement learning
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Edwin P. D. Pednault, Naoki Abe, Bianca Zadrozny