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Approximations in Distributed Optimization

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Sampling can be faster than optimization

Nicolas Henri Bernard Flammarion

Optimization algorithms and Monte Carlo sampling algorithms have provided the computational foundations for the rapid growth in applications of statistical machine learning in recent years. There is, however, limited theoretical understanding of the relati ...

PNAS2019

The Complexity of Splitting Necklaces and Bisecting Ham Sandwiches

Aris Filos Ratsikas

We resolve the computational complexity of two problems known as NECKLACE-SPLITTING and DISCRETE HAM SANDWICH, showing that they are PPA-complete. For NECKLACE SPLITTING, this result is specific to the important special case in which two thieves share the ...

ACM2019

Stable Fractional Matchings

Aris Filos Ratsikas

We study a generalization of the classical stable matching problem that allows for cardinal preferences (as opposed to ordinal) and fractional matchings (as opposed to integral). After observing that, in this cardinal setting, stable fractional matchings c ...

2019

Stable Fractional Matchings

Aris Filos Ratsikas

ASSOC COMPUTING MACHINERY2019

Fast assembly of Galerkin matrices for 3D solid laminated composites using finite element and isogeometric discretizations

Pablo Antolin Sanchez

This work presents a novel methodology for speeding up the assembly of stiffness matrices for laminate composite 3D structures in the context of isogeometric and finite element discretizations. By splitting the involved terms into their in-plane and out-of ...

2019

The complexity of error metrics

Mathias Soeken

Approximate computing exploits the fact that many applications do not require the results to be exact but not to exceed a threshold in a given error metric. Algorithms in approximate computing require to compute the error of the approximation in order to m ...

ELSEVIER SCIENCE BV2018

The Linear Programming Approach to Reach-Avoid Problems for Markov Decision Processes

Maryam Kamgarpour, John Lygeros, Tyler Summers

One of the most fundamental problems in Markov decision processes is analysis and control synthesis for safety and reachability specifications. We consider the stochastic reach-avoid problem, in which the objective is to synthesize a control policy to max ...

2017

Optimal Representations for Adaptive Streaming in Interactive Multiview Video Systems

Pascal Frossard, Laura Toni

Interactive multiview video streaming (IMVS) services permit to remotely navigate within a 3D scene with an immersive experience. This is possible by transmitting a set of reference camera views (anchor views), which are used by the clients to freely navig ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

-TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...

SIAM2016

Fast Robust PCA on Graphs

Pierre Vandergheynst, Gilles Puy, Nathanaël Perraudin, Nauman Shahid, Vasilis Kalofolias

Mining useful clusters from high dimensional data has received significant attention of the computer vision and pattern recognition community in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome the c ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

SIAM2016