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In this note we re-evaluate the Eurocrypt’16 paper by Zhang et al. [9] in the area of LPN solving algorithms. We present the history of LPN solving algorithms and give the general description of the algorithm from [9]. While this new algorithm claims to im ...
In free viewpoint video, a viewer can choose at will any camera angle or the so-called "virtual view" to observe a dynamic 3-D scene, enhancing his/her depth perception. The virtual view is synthesized using texture and depth videos of two anchor camera vi ...
We propose an asynchronous, decentralized algorithm for consensus optimization. The algorithm runs over a network of agents, where the agents perform local computation and communicate with neighbors. We design the algorithm so that the agents can compute a ...
We give a randomized 2^{n+o(n)}-time and space algorithm for solving the Shortest Vector Problem (SVP) on n-dimensional Euclidean lattices. This improves on the previous fastest algorithm: the deterministic O(4^n)-time and O(2^n)-space algorithm of Miccian ...
A wide variety of problems in machine learning, including exemplar clustering, document summarization, and sensor placement, can be cast as constrained submodular maximization problems. A lot of recent effort has been devoted to developing distributed algo ...
The Learning With Error problem (LWE) is becoming more and more used in cryptography, for instance, in the design of some fully homomorphic encryption schemes. It is thus of primordial importance to find the best algorithms that might solve this problem so ...
We consider the capacitated -center problem. In this problem we are given a finite set of locations in a metric space and each location has an associated non-negative integer capacity. The goal is to choose (open) locations (called centers) and assign each ...
We design a sublinear Fourier sampling algorithm for a case of sparse off-grid frequency recovery. These are signals with the form ; i.e., exponential polynomials with a noise term. The frequencies satisfy and for some . We design a sublinear time randomiz ...
We propose a recursive algorithm for estimating time-varying signals from a few linear measurements. The signals are assumed sparse, with unknown support, and are described by a dynamical model. In each iteration, the algorithm solves an ℓ1-ℓ1 minimization ...
We investigate the nonsmooth and nonconvex L-1-Potts functional in discrete and continuous time. We show Gamma-convergence of discrete L-1-Potts functionals toward their continuous counterpart and obtain a convergence statement for the corresponding minimi ...
