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A Blockwise Descent Algorithm for Group-penalized Multiresponse and Multinomial Regression
Blockwise Descent Algorithm Group-penalized Multiresponse Multinomial Regression
2015/8/21
In this paper we purpose a blockwise descent algorithm for grouppenalized multiresponse regression. Using a quasi-newton framework we extend this to group-penalized multinomial regression. We give a p...
An Adaptive Sequential Monte Carlo Algorithm for Computing Permanents
Sequential Monte Carlo Permanents Relative Variance
2013/6/14
We consider the computation of the permanent of a binary n by n matrix. It is well- known that the exact computation is a #P complete problem. A variety of Markov chain Monte Carlo (MCMC) computationa...
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
Divide and Conquer Kernel Ridge Regression A Distributed Algorithm Minimax Optimal Rates
2013/6/14
We establish optimal convergence rates for a decomposition-based scalable approach to kernel ridge regression. The method is simple to describe: it randomly partitions a dataset of size N into m subse...
An Improved EM algorithm
Sensitivity analysis Convergence analysis Expectation Maximization K-means K-medoids
2013/6/14
In this paper, we firstly give a brief introduction of expectation maximization (EM) algorithm, and then discuss the initial value sensitivity of expectation maximization algorithm. Subsequently, we g...
Heart Disease Prediction System using Associative Classification and Genetic Algorithm
Andhra Pradesh Associative classification Genetic algorithm Gini Index Z-Statistics
2013/5/2
Associative classification is a recent and rewarding technique which integrates association rule mining and classification to a model for prediction and achieves maximum accuracy. Associative classifi...
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems
A General Iterative Shrinkage Thresholding Algorithm Non-convex Regularized Optimization Problems
2013/5/2
Non-convex sparsity-inducing penalties have recently received considerable attentions in sparse learning. Recent theoretical investigations have demonstrated their superiority over the convex counterp...
On the convergence of the IRLS algorithm in Non-Local Patch Regression
Non-local means non-local patch regression,ℓ p minimization non-convex optimization iteratively reweighted least-squares majorize-minimize stationary point relaxation sequence linear convergence
2013/4/28
Recently, it was demonstrated in [CS2012,CS2013] that the robustness of the classical Non-Local Means (NLM) algorithm [BCM2005] can be improved by incorporating $\ell^p (0 < p \leq 2)$ regression into...
Almost sure convergence and asymptotical normality of a generalization of Kesten's stochastic approximation algorithm for multidimensional case
Kesten's stochastic approximation algorithm multidimensional
2011/6/20
It is shown the almost sure convergence and asymptotical normality of a generalization of
Kesten's stochastic approximation algorithm for multidimensional case.
In this generalization, the step incr...
Interpreting Graph Cuts as a Max-Product Algorithm
Max-Product Interpreting Graph binary variable models
2011/6/16
The maximum a posteriori (MAP) con guration
of binary variable models with submodular
graph-structured energy functions
can be found eciently and exactly by graph
cuts. Max-product belief propaga...