In this paper we generalize the framework of the feasible descent method (FDM) to a randomized (R-FDM) and a coordinate-wise random feasible descent method (RC-FDM) framework. We show that the famous SDCA algorithm for optimizing the SVM dual problem, or the stochastic coordinate descent method for the LASSO problem, fits into the framework of RC-FDM. We prove linear convergence for both R-FDM ...

In this paper we generalize the framework of the Feasible Descent Method (FDM) to a Randomized (R-FDM) and a Randomized Coordinate-wise Feasible Descent Method (RCFDM) framework. We show that many machine learning algorithms, including the famous SDCA algorithm for optimizing the SVM dual problem, or the stochastic coordinate descent method for the LASSO problem, fits into the framework of RC-F...

This paper describes an approach to the use of gradient descent search in genetic programming for continuously evolving genetic programs for object classification problems. An inclusion factor is introduced to each node in a genetic program and gradient descent search is applied to the inclusion factors. Three new on-zero operators and two new continuous genetic operators are developed for evol...

Cyclic coordinate descent is a classic optimization method that has witnessed a resurgence of interest in Signal Processing, Statistics and Machine Learning. Reasons for this renewed interest include the simplicity, speed, and stability of the method as well as its competitive performance on `1 regularized smooth optimization problems. Surprisingly, very little is known about its non-asymptotic...

The satissability (SAT) problem is a basic problem in computing theory. Presently, an active area of research on SAT problem is to design eecient optimization algorithms for nding a solution for a satissable CNF formula. A new formulation, the Universal SAT problem model, which transforms the SAT problem on Boolean space into an optimization problem on real space has been developed 31, 35, 34, ...

Recently, we have demonstrated a new and efficient method to simultaneously reconstruct two unknown interfering wavefronts. A three-dimensional interference pattern was analyzed and then Zernike polynomials and the stochastic parallel gradient descent algorithm were used to expand and calculate wavefronts. In this paper, as one of the applications of this method, the reflected wavefronts from t...

the myth of the descent of adam, with all its complexities, has being preoccupied the mind of human kind from the very beginning stages of creation. the holy books of torah, bible and quran have each paid to different angles of this legend. studying the modern poetry, it can be found that the contemporary poets have been under the influence of quran and have used the teachings of old and new te...

background: in most of defecography films, the symphysis pubis is obscured, especially in obese patients, and the parameters will change in values if x-ray is interpreted by different reviewers or if the patient changes his/her position between the phases. this study was carried out to determine how to do the defecography to obtain fixed parameters. â  methods: eighty patients that had been can...

We present a novel learning-based method for generating optimal motion plans for high-dimensional motion planning problems. In order to cope with the curse of dimensionality, our method proceeds in a fashion similar to block coordinate descent in finite-dimensional optimization: at each iteration, the motion is optimized over a lower dimensional subspace while leaving the path fixed along the o...

In this paper, we make a modification to the LS conjugate gradient method and propose a descent LS method. The method can generates sufficient descent direction for the objective function. We prove that the method is globally convergent with an Armijo-type line search. Moreover, under mild conditions, we show that the method is globally convergent if the Armijo line search or the Wolfe line sea...