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» The Convergence of Iterated Classification
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SIAMJO
2010
87views more  SIAMJO 2010»
13 years 9 months ago
A Second Derivative SQP Method: Global Convergence
Abstract. Sequential quadratic programming (SQP) methods form a class of highly efficient algorithms for solving nonlinearly constrained optimization problems. Although second deri...
Nicholas I. M. Gould, Daniel P. Robinson
KDD
2009
ACM
215views Data Mining» more  KDD 2009»
14 years 11 months ago
Large-scale sparse logistic regression
Logistic Regression is a well-known classification method that has been used widely in many applications of data mining, machine learning, computer vision, and bioinformatics. Spa...
Jun Liu, Jianhui Chen, Jieping Ye
SIAMIS
2011
13 years 6 months ago
Gradient-Based Methods for Sparse Recovery
The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
William W. Hager, Dzung T. Phan, Hongchao Zhang

Publication
334views
14 years 8 months ago
Rollout Sampling Approximate Policy Iteration
Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schem...
Christos Dimitrakakis, Michail G. Lagoudakis
KDD
1995
ACM
109views Data Mining» more  KDD 1995»
14 years 2 months ago
An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers
The Bayesianclassifier is a simple approachto classification that producesresults that are easy for people to interpret. In many cases, the Bayesianclassifieris at leastasaccurate...
Michael J. Pazzani