The use of semileptonic decays has become standard in constraining the unitarity triangle. Since precise calculations of these are very challenging, we propose an entirely new approach. The ε{K} constraint, which depends extremely sensitively on |V{cb}|, is replaced by the interplay between ε{K}, BR(B→τν), and ΔM{B{s}}. Improvements on the B→τν branching ratio and on the lattice determinations ...

We investigate the problem of estimating a random variable Y ∈ Y under a privacy constraint dictated by another correlated random variable X ∈ X , where estimation efficiency and privacy are assessed in terms of two different loss functions. In the discrete case, we use the Hamming loss function and express the corresponding utility-privacy tradeoff in terms of the privacy-constrained guessing ...

Data backup in data center networks (DCNs) is critical to minimize the data loss under disaster. This paper considers the cost-efficient data backup for DCNs against a disaster with ε early warning time. Given geo-distributed DCNs and such a ε-time early warning disaster, we investigate the issue of how to back up the data in DCN nodes under risk to other safe DCN nodes within the ε early warni...

The ε constrained method is an algorithm transformation method, which can convert algorithms for unconstrained problems to algorithms for constrained problems using the ε level comparison, which compares search points based on the pair of objective value and constraint violation of them. We have proposed the ε constrained differential evolution εDE, which is the combination of the ε constrained...

In this paper, we study scalable algorithms for influence maximization with general marketing strategies (IM-GMS), in which a marketing strategy mix is modeled as a vector x = (x1, . . . , xd) and could activate a node v in the social network with probability hv(x). The IM-GMS problem is to find the best strategy mix x∗ that maximize the influence spread due to influence propagation from the ac...

A unique game is a type of constraint satisfaction problem with two variables per constraint. The value of a unique game is the fraction of the constraints satisfied by an optimal solution. Khot (STOC’02) conjectured that for arbitrarily small γ,ε > 0 it is NPhard to distinguish games of value smaller than γ from games of value larger than 1− ε . Several recent inapproximability results rely on...

We consider the Cauchy problem for 2-D incompressible isotropic elastodynamics. Standard energy methods yield local solutions on a time interval [0, T/ε] for initial data of the form εU0, where T depends only on some Sobolev norm of U0. We show that for such data there exists a unique solution on a time interval [0, exp T/ε], provided that ε is sufficiently small. This is achieved by careful co...

In this paper, we study the theoretical properties of a class of iteratively re-weighted least squares (IRLS) algorithms for sparse signal recovery in the presence of noise. We demonstrate a one-to-one correspondence between this class of algorithms and a class of Expectation-Maximization (EM) algorithms for constrained maximum likelihood estimation under a Gaussian scale mixture (GSM) distribu...

This work addresses the limits on the information that can be transmitted over the wireless channel under the conditions stated by the MAC layer: a selected scheduling discipline and an ensured level of QoS. Based on the effective bandwidth theory, the joint influence of the channel fading, the data outsourcing process, and the scheduling discipline in the QoS metrics are studied. We obtain a c...

Let Z(F ) be the number of solutions of a random k-satisfiability formula F with n variables and clause density α. Assume that the probability that F is unsatisfiable is O(1/ log(n)) for some δ > 0. We show that (possibly excluding a countable set of ‘exceptional’ α’s) the normalized logarithm of the number of solutions concentrates, i.e., there exists a non-random function α 7→ φs(α) such that...