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Centrality of Trees for Capacitated k-Center

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Submodular Stochastic Probing on Matroids

Justin Dean Ward, Marek Adamczyk

In a stochastic probing problem we are given a universe E, and a probability that each element e in E is active. We determine if an element is active by probing it, and whenever a probed element is active, we must permanently include it in our solution. Mo ...

INFORMS2016

Centrality of trees for capacitated -center

Ola Nils Anders Svensson, Hyung Chan An, Aditya Bhaskara

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 ...

Springer Heidelberg2015

Solving the Shortest Vector Problem in 2^n Time via Discrete Gaussian Sampling

Divesh Aggarwal

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 ...

ACM2015

Approximating ATSP by Relaxing Connectivity

Ola Nils Anders Svensson

The standard LP relaxation of the asymmetric traveling salesman problem has been conjectured to have a constant integrality gap in the metric case. We prove this conjecture when restricted to shortest path metrics of node-weighted digraphs. Our arguments a ...

IEEE Computer Society2015

Improving Christofides' Algorithm for the s-t Path TSP

Hyung Chan An

We present a deterministic (1+root 5/2)-approximation algorithm for the s-t path TSP for an arbitrary metric. Given a symmetric metric cost on n vertices including two prespecified endpoints, the problem is to find a shortest Hamiltonian path between the t ...

Assoc Computing Machinery2015

Adaptation and Awareness in Robot Ensembles: Scenarios and Algorithms

Francesco Mondada, Michael Bonani

This chapter presents a disaster recovery scenario that has been used throughout the ASCENS project as a reference to coordinate the study of distributed algorithms for robot ensembles. We first introduce the main traits and open problems in the design of ...

Springer2015

On the configuration LP for maximum budgeted allocation

Ola Nils Anders Svensson, Christos Kalaitzis, Lukas Polacek, Aleksander Madry

We study the maximum budgeted allocation problem, i.e., the problem of selling a set of m indivisible goods to n players, each with a separate budget, such that we maximize the collected revenue. Since the natural assignment LP is known to have an integral ...

Springer Heidelberg2015

Better Algorithms for LWE and LWR

Serge Vaudenay, Alexandre Raphaël Duc, Florian Tramèr

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 ...

Springer2015

Dynamic Sparse State Estimation Using ℓ1-ℓ1 Minimization: Adaptive-rate Measurement Bounds, Algorithms and Applications

Volkan Cevher

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 ...

2015

Sensing the real world

Juri Ranieri

A sensor is a device that detects or measures a physical property and records, indicates, or otherwise responds to it. In other words, a sensor allows us to interact with the surrounding environment, by measuring qualitatively or quantitatively a given phe ...

EPFL2014