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» Learning to learn with the informative vector machine
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COLT
2005
Springer
15 years 10 months ago
Trading in Markovian Price Models
We examine a Markovian model for the price evolution of a stock, in which the probability of local upward or downward movement is arbitrarily dependent on the current price itself...
Sham M. Kakade, Michael J. Kearns
DGO
2004
110views Education» more  DGO 2004»
15 years 5 months ago
Question Answering Performance on Table Data
Question answering (QA) on table data is a challenging information retrieval task. This paper describes a QA system for tables created with both machine learning and heuristic tab...
Xing Wei, W. Bruce Croft, David Pinto
TKDE
2008
152views more  TKDE 2008»
15 years 4 months ago
SRDA: An Efficient Algorithm for Large-Scale Discriminant Analysis
Linear Discriminant Analysis (LDA) has been a popular method for extracting features that preserves class separability. The projection functions of LDA are commonly obtained by max...
Deng Cai, Xiaofei He, Jiawei Han
CAI
1999
Springer
15 years 4 months ago
Context in Artificial Intelligence: I. A Survey of the Literature
: Context is the challenge for the coming years in Artificial Intelligence. In the companion paper [8], we present the main results of discussions at two workshops and at the first...
Patrick Brézillon
ICDM
2008
IEEE
160views Data Mining» more  ICDM 2008»
15 years 11 months ago
Direct Zero-Norm Optimization for Feature Selection
Zero-norm, defined as the number of non-zero elements in a vector, is an ideal quantity for feature selection. However, minimization of zero-norm is generally regarded as a combi...
Kaizhu Huang, Irwin King, Michael R. Lyu