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IOR
2006
163views more  IOR 2006»
13 years 7 months ago
Adaptive Importance Sampling Technique for Markov Chains Using Stochastic Approximation
For a discrete-time finite-state Markov chain, we develop an adaptive importance sampling scheme to estimate the expected total cost before hitting a set of terminal states. This s...
T. P. I. Ahamed, Vivek S. Borkar, S. Juneja
ICDM
2006
IEEE
108views Data Mining» more  ICDM 2006»
14 years 1 months ago
Minimum Enclosing Spheres Formulations for Support Vector Ordinal Regression
We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples. B...
Shirish Krishnaj Shevade, Wei Chu
ICDT
2009
ACM
119views Database» more  ICDT 2009»
14 years 8 months ago
Analysis of sampling techniques for association rule mining
In this paper, we present a comprehensive theoretical analysis of the sampling technique for the association rule mining problem. Most of the previous works have concentrated only...
Venkatesan T. Chakaravarthy, Vinayaka Pandit, Yogi...
ECCV
2006
Springer
14 years 9 months ago
Sampling Strategies for Bag-of-Features Image Classification
Abstract. Bag-of-features representations have recently become popular for content based image classification owing to their simplicity and good performance. They evolved from text...
Eric Nowak, Frédéric Jurie, Bill Tri...
NIPS
2008
13 years 9 months ago
On the Reliability of Clustering Stability in the Large Sample Regime
Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
Ohad Shamir, Naftali Tishby