The present study is an attempt toward evaluating the performance of portfolios and assets selecting using modified mean-variance models by utilizing a non-parametric efficiency analysis tool, namely Data Envelopment Analysis (DEA). Huge amounts of money are being invested in financial market. As a result, portfolio performance evaluation has created a great deal of interest among people. We kn...

The estimation of variance-covariance matrices in situations that involve the optimization of an objective function (e.g. a log-likelihood function) is usually a difficult numerical problem, since the resulting estimates should be positive semi-definite matrices. We can either use constrained optimization, or employ a parameterization that enforces this condition. We describe here five differen...

Given a multidimensional data set, a skyline query returns the interesting points that are not dominated by other points. The actual cardinality (s) of a skyline query result may vary substantially from the desired result cardinality (k). An approach called skyline ordering is used that forms a skyline based partitioning of a given data set, it provides an ordering among the partitions. The con...

This paper presents a performance comparison between a constrained least mean squared algorithm for MIMO CDMA decision feedback equalizer and linear equalizer. Both algorithms are constrained on the length of spreading sequence, number of users, variance of multiple access interference as well as additive white Gaussian noise (new constraint). An important feature of both algorithms is that mul...

We design and analyze Variance-Aware-Lower Upper Confidence Bound (VA-LUCB), a parameter-free algorithm, for identifying the best arm under fixed-confidence setup stringent constraint that variance of chosen is strictly smaller than given threshold. An upper bound on VA-LUCB’s sample complexity shown to be characterized by fundamental variance-aware hardness quantity <inline-formula xmlns:mml="...