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Digital art

Related publications (101)

Robustness via curvature regularization, and vice versa

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Alhussein Fawzi

State-of-the-art classifiers have been shown to be largely vulnerable to adversarial perturbations. One of the most effective strategies to improve robustness is adversarial training. In this paper, we investigate the effect of adversarial training on the ...

IEEE2019

Functional Decomposition Using Majority

Giovanni De Micheli, Mathias Soeken, Zhufei Chu

Typical operators for the decomposition of Boolean functions in state-of-the-art algorithms are AND, exclusive-OR (XOR), and a 2-to-1 multiplexer (MUX). We propose a logic decomposition algorithm that uses the majority-of-three (MAJ) operation. Such decomp ...

ASSOC COMPUTING MACHINERY2018

Functional Decomposition Using Majority

Giovanni De Micheli, Mathias Soeken, Zhufei Chu

IEEE2018

SNM: Stochastic Newton Method for Optimization of Discrete Choice Models

Michel Bierlaire, Virginie Janine Camille Lurkin, Gael Lederrey

Optimization algorithms are rarely mentioned in the discrete choice literature. One reason may be that classic Newton-Raphson methods have been rather successful in estimating discrete choice parameters on available data sets of limited size. However, than ...

2018

SNM: Stochastic Newton Methodfor Optimization of Discrete Choice Models

Michel Bierlaire, Virginie Janine Camille Lurkin, Gael Lederrey

IEEE2018

Indiscreet logarithms in finite fields of small characteristic

Robert Granger, Thorsten Kleinjung, Jens Markus Zumbrägel

Recently, several striking advances have taken place regarding the discrete logarithm problem (DLP) in finite fields of small characteristic, despite progress having remained essentially static for nearly thirty years, with the best known algorithms being ...

2018

Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching.

François Fleuret, Anton Ivanov, Stepan Tulyakov

End-to-end deep-learning networks recently demonstrated extremely good performance for stereo matching. However, existing networks are difficult to use for practical applications since (1) they are memory-hungry and unable to process even modest-size image ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Robustness via curvature regularization, and vice versa

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Alhussein Fawzi

2018

Outdoor comfort simulation of complex architectural designs: a review of simulation tools from the designer perspective.

Jean-Louis Scartezzini, Silvia Coccolo, Emanuele Naboni

The expanding design interest in outdoor comfort design is today supported by a few software tools. Given their different user-friendliness, modelling environments and simulation engines, a rational inquiry is how they are integrated into the digital desig ...

2018

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization

Volkan Cevher, Quoc Tran Dinh, Ahmet Alacaoglu

We propose a new randomized coordinate descent method for a convex optimization template with broad applications. Our analysis relies on a novel combination of four ideas applied to the primal-dual gap function: smoothing, acceleration, homotopy, and coord ...

2017

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