Publications related to Algorithm

Bayesian Decision Making in Groups is Hard

We study the computations that Bayesian agents undertake when exchanging opinions over a network. The agents act repeatedly on their private information and take myopic actions that maximize their expected utility according to a fully rational posterior be ...

INFORMS2021

Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search

Mathieu Salzmann, Kaicheng Yu

Weight sharing has become a de facto standard in neural architecture search because it enables the search to be done on commodity hardware. However, recent works have empirically shown a ranking disorder between the performance of stand-alone architectures ...

IEEE COMPUTER SOC2021

A first-order primal-dual method with adaptivity to local smoothness

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni

Many image-based perception tasks can be formulated as detecting, associating and tracking semantic keypoints, e.g., human body pose estimation and tracking. In this work, we present a general framework that jointly detects and forms spatio-temporal keypoi ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Sulaiman A S A E Alghunaim

This article studies a class of nonsmooth decentralized multiagent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a common nonsmooth term. We propose a general primal-dual algorithmic framewor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

The role of PDE-based parameterization techniques in gradient-based IGA shape optimization applications

This paper proposes a shape optimization algorithm based on the principles of Isogeometric Analysis (IGA) in which the parameterization of the geometry enters the problem formulation as an additional PDE-constraint. Inspired by the isoparametric principle ...

2021

ON THE DESIGN AND OPTIMIZATION OF WIDE ANGLE DIFFRACTIVE OPTICAL ELEMENTS

Dong Cheon Kim

Diffractive optical elements (DOEs) which consist of microstructure surface relief permit the generation of the spatial distribution of light beams by using a single element. Due to their compact size, design flexibility, and mass productivity, they are us ...

EPFL2021

How to Match in Modern Computational Settings

Buddhima Ruwanmini Gamlath Gamlath Ralalage

This thesis focuses on the maximum matching problem in modern computational settings where the algorithms have to make decisions with partial information.First, we consider two stochastic models called query-commit and price-of-information where the algori ...

EPFL2021

Is there an analog of Nesterov acceleration for gradient-based MCMC?

Nicolas Henri Bernard Flammarion, Xiang Cheng

We formulate gradient-based Markov chain Monte Carlo (MCMC) sampling as optimization on the space of probability measures, with Kullback-Leibler (KL) divergence as the objective functional. We show that an under-damped form of the Langevin algorithm perfor ...

INT STATISTICAL INST2021

Evading Voltage-Based Intrusion Detection on Automotive CAN

Mathias Josef Payer, Duo Xu, Rohit Bhatia

The controller area network (CAN) is widely adopted in modern automobiles to enable communications among in-vehicle electronic control units (ECUs). Lacking mainstream network security capabilities due to resource constraints, the CAN is susceptible to the ...

INTERNET SOC2021

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Bayesian Decision Making in Groups is Hard

Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search

A first-order primal-dual method with adaptivity to local smoothness

OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

The role of PDE-based parameterization techniques in gradient-based IGA shape optimization applications

ON THE DESIGN AND OPTIMIZATION OF WIDE ANGLE DIFFRACTIVE OPTICAL ELEMENTS

How to Match in Modern Computational Settings

Is there an analog of Nesterov acceleration for gradient-based MCMC?

Evading Voltage-Based Intrusion Detection on Automotive CAN

ON THE DESIGN AND OPTIMIZATION OF WIDE ANGLE DIFFRACTIVE OPTICAL ELEMENTS

Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search

Bayesian Decision Making in Groups is Hard

The role of PDE-based parameterization techniques in gradient-based IGA shape optimization applications

How to Match in Modern Computational Settings

OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Is there an analog of Nesterov acceleration for gradient-based MCMC?

Evading Voltage-Based Intrusion Detection on Automotive CAN

A first-order primal-dual method with adaptivity to local smoothness