This paper investigates the following natural greedy procedure for clustering in the bi-criterion setting: iteratively grow a set of centers, in each round adding the center from a candidate set that maximally decreases clustering cost. In the case of k-medians and k-means, the key results are as follows. • When the method considers all data points as candidate centers, then selecting O(k log(1...

We propose a first order interior point algorithm for a class of nonLipschitz and nonconvex minimization problems with box constraints, which arise from applications in variable selection and regularized optimization. The objective functions of these problems are continuously differentiable typically at interior points of the feasible set. Our first order algorithm is easy to implement and the ...

It is well-known that in combination with further premises that look less controversial, the tolerance principle – the constraint that if Pa holds, and a and b are similar in P -relevant respects, Pb holds as well – leads to contradiction, namely to the sorites paradox. According to many influential views of the sorites paradox (e.g. Williamson 1994), we therefore ought to reject the principle ...

The complexity and approximability of the constraint satisfaction problem (CSP) has been actively studied over past 20 years. A new version CSP, promise CSP (PCSP), recently proposed, motivated by open questions about variants satisfiability graph colouring. PCSP significantly extends standard decision CSP. CSPs with a fixed language on finite domain fully classified, greatly guided algebraic a...

this work focuses on the correction of both the coecient and the right hand side matrices of the inconsistent matrix equations $ax = b$ and $xc = d$ with orthogonal constraint. by optimal correction approach, a general representation of the orthogonal solution is obtained. this method is tested on two examples to show that the optimal correction is eective and highly accurate.

We present efficient distributed δ-approximation algorithms for fractional packing and maximum weighted b-matching in hypergraphs, where δ is the maximum number of packing constraints in which a variable appears (for maximum weighted b-matching δ is the maximum edge degree — for graphs δ = 2). (a) For δ = 2 the algorithm runs in O(logm) rounds in expectation and with high probability. (b) For g...

Inversion of magnetic data is an important step towards interpretation of the practical data. Smooth inversion is a common technique for the inversion of data. Physical bound constraint can improve the solution to the magnetic inverse problem. However, how to introduce the bound constraint into the inversion procedure is important. Imposing bound constraint makes the magnetic data inversion a n...

In this paper, a displacement-constrained volume-minimizing topology optimization model is present for two-dimensional continuum problems. The new model is a generalization of the displacement-constrained volume-minimizing model developed by Yi and Sui [1] in which the displacement is constrained in the loading point. In the original model the displacement constraint was formulated as an equali...