A harmonic framework for stepsize selection in gradient methods

Modified Two-Point Stepsize Gradient Methods for Unconstrained Optimization

a framework for identifying and prioritizing factors affecting customers’ online shopping behavior in iran

the purpose of this study is identifying effective factors which make customers shop online in iran and investigating the importance of discovered factors in online customers’ decision. in the identifying phase, to discover the factors affecting online shopping behavior of customers in iran, the derived reference model summarizing antecedents of online shopping proposed by change et al. was us...

A New Framework for Distributed Multivariate Feature Selection

Feature selection is considered as an important issue in classification domain. Selecting a good feature through maximum relevance criterion to class label and minimum redundancy among features affect improving the classification accuracy. However, most current feature selection algorithms just work with the centralized methods. In this paper, we suggest a distributed version of the mRMR featu...

Stepsize Selection for Approximate Value Iteration and a New Optimal Stepsize Rule

Approximate value iteration is used in dynamic programming when we use random observations to estimate the value of being in a state. These observations are smoothed to approximate the expected value function, leading to the problem of choosing a stepsize (the weight given to the most recent observation). A stepsize of 1/n is a common (and provably convergent) choice. However, we prove that it ...

Convergence of Conjugate Gradient Methods with a Closed-Form Stepsize Formula

Conjugate gradient methods are efficient methods for minimizing differentiable objective functions in large dimension spaces. However, converging line search strategies are usually not easy to choose, nor to implement. Sun and colleagues (Ann. Oper. Res. 103:161–173, 2001; J. Comput. Appl. Math. 146:37–45, 2002) introduced a simple stepsize formula. However, the associated convergence domain ha...