An efficient Actionable 3D Subspace Clustering based on Optimal Centroids from continuous valued data represented three dimensionally which is suitable for real world problems profitable stocks discovery , biologically significant protein residues etc. It achieves actionable patterns ,incorporation of domain knowledge which allows users to choose the preferred utility(profit/benefit) function, ...

in this paper mathematical structure of time-dependent lagrangian systems and their symmetries are extended and the explicit relation between constants of motion and infinitesimal symmetries of time-dependent lagrangian systems are considered. starting point is time-independent lagrangian systems ,then we extend mathematical concepts of these systems such as equivalent lagrangian systems to the...

For the best-choice (or secretary) problem with an unknown number N of objects, minimax-optimal strategies for the observer and minimax distributions for N are derived under the assumption that N is a random variable with expected value at most M, where M is known. The solution is derived as a special case of the situation where N is constrained by Ef(N) <_ M, where f is increasing with f(i) f(...

This paper presents a global optimization method for structural design optimization, which integrates subset simulation optimization (SSO) and the dynamic augmented Lagrangian multiplier method (DALMM). The proposed method formulates the structural design optimization as a series of unconstrained optimization sub-problems using DALMM and makes use of SSO to find the global optimum. The combined...

This report considers the solution of estimation problems based on the maximum likelihood principle when a xed number of equality constraints are imposed on the problem. Consistency and the asymptotic distribution of the parameter estimates as n ! 1, where n is the number of observations, are discussed, and it is shown that a suitably scaled limiting multiplier vector is known. It is suggested ...

A complexity reduction algorithm for an H.264 encoder is proposed. Computational savings are achieved by identifying, prior to motion estimation, macroblocks that are likely to be skipped and hence saving further computational processing of these macroblocks. This early prediction is made by estimating a Lagrangian rate-distortion cost function which incorporates an adaptive model for the Lagra...

We present a new inversion approach, in which the Lagrangian multiplier is set as a variable at each parameterized blocks and automatically determined according to the parameter resolution matrix and spread function analysis. The approach, named Active Constraint Balancing (ACB), tries to balance the constraints of the optimization according to sensitivity for a given problem so that it enhance...

This article develops analytical models for a class of networking problems that includes two cascaded stages of demand aggregation and capacity allocation. The solutions to these problems are required in real time as the demand fluctuates rapidly. The capacity allocation problem makes a large-scale integer programming problem too complex for practical applications. Using the Lagrangian relaxati...

Abstract. We study the prize-collecting version of the Node-weighted Steiner Tree problem (NWPCST) restricted to planar graphs. We give a new primal-dual Lagrangian-multiplier-preserving (LMP) 3-approximation algorithm for planar NWPCST. We then show a (2.88+ǫ)-approximation which establishes a new best approximation guarantee for planar NWPCST. This is done by combining our LMP algorithm with ...

This paper introduces a genetic algorithm enhanced with a trap escaping strategy derived from the dual information presented as discrete Lagrange multipliers. When the genetic algorithm is trapped into a local optima, the Discrete Lagrange Multiplier method is called for the best individual found. The information provided by the Lagrangian method is unified, in the form of recombination, with t...