Publications associées à State space search

Efficient Massively Parallel Join Optimization for Large Queries

Anastasia Ailamaki, Bikash Chandra, Srinivas Karthik Venkatesh, Riccardo Mancini, Vasileios Mageirakos

Modern data analytical workloads often need to run queries over a large number of tables. An optimal query plan for such queries is crucial for being able to run these queries within acceptable time bounds. However, with queries involving many tables, find ...

ACM2022

Actuator Layout Optimization for Adaptive Structures Performing Large Shape Changes, Advanced Computing Strategies for Engineering

Ian Smith, Gennaro Senatore, Arka Prabhata Reksowardojo

Adaptive structures are sensed and actuated to modify internal forces and shape to maintain optimal performance in response to loads. The use of large shape changes as a structural adaptation strategy to counteract the effect of loads has been investigated ...

2018

Riemannian Optimization for Solving High-Dimensional Problems with Low-Rank Tensor Structure

Michael Maximilian Steinlechner

In this thesis, we present a Riemannian framework for the solution of high-dimensional optimization problems with an underlying low-rank tensor structure. Here, the high-dimensionality refers to the size of the search space, while the cost function is scal ...

EPFL2016

Memetic Viability Evolution for Constrained Optimization

Dario Floreano, Andrea Maesani, Giovanni Iacca

The performance of evolutionary algorithms can be heavily undermined when constraints limit the feasible areas of the search space. For instance, while Covariance Matrix Adapta- tion Evolution Strategy is one of the most efficient algorithms for unconstrai ...

Institute of Electrical and Electronics Engineers2016

Tractable Approaches to Learning and Planning in High Dimensions

Leonidas Lefakis

The continuous increase, witnessed in the last decade, of both the amount of available data and the areas of application of machine learning, has lead to a demand for both learning and planning algorithms that are capable of handling large-scale problems. ...

EPFL2014

Optimization Methodology of Dynamic Data Structures Based on Genetic Algorithms for Multimedia Embedded Systems

David Atienza Alonso, José Luis Risco Martin

Modern multimedia application exhibit high resource utilization. In order to efficiently run this kind of applications in embedded systems, the dynamic memory subsystem needs to be optimized. A key role in this optimization is played by the dynamic data st ...

2009

Variable space search for graph coloring

Nicolas Zufferey, Matthieu Plumettaz

Let G = (V, E) be a graph with vertex set V and edge set E. The k-coloring problem is to assign a color (a number chosen in {1, ..., k}) to each vertex of G so that no edge has both endpoints with the same color. We propose a new local search methodology, ...

2008

A multiple birthday attack on NTRU

In this paper we view the possibilities to lance a multiple (iterative) birthday attack on NTRU. Recently Wagner's algorithm for the generalized birthday problem (Wagner, 2002) allowed to speed-up several combinatorial attacks. However, in the case of NTRU ...

Insticc-Inst Syst Technologies Information Control & Communication, Avenida D Manuel L, 27A 2 Esquerdo, Setubal, 2910-595, Portugal2008

The virtue of patience in low complexity scheduling of packetized media with feedback

Pascal Frossard, Christophe De Vleeschouwer

We consider streaming of pre-encoded and packetized media over best-effort networks in presence of acknowledgment feedbacks. We first review the rate-distortion optimization framework in such scenarios. Given an estimation of future transmission resources, ...

2007

3D analysis and optimization of microwave circuits by the method of moments

Francisco Jesus Nunez

The design and minaturization of microwave circuits involves the analysis and optimization of a large varity of structures, which, in general, are based on arbritrary objects embedded in also arbritary media. The most common situation is found when optimiz ...

EPFL2006

Kernel Matching Pursuit for Large Datasets

Jean-Philippe Thiran, Vlad Popovici

Kernel matching pursuit is a greedy algorithm for building an approximation of a discriminant function as a linear combination of some basis functions selected from a kernel-induced dictionary. Here we propose a modification of the kernel matching pursuit ...

2005