Publications related to Essays in Empirical Asset Pricing

Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

Pascal Fua, Mathieu Salzmann, Agata Justyna Mosinska, Mateusz Kozinski

The difficulty of obtaining annotations to build training databases still slows down the adoption of recent deep learning approaches for biomedical image analysis. In this paper, we show that we can train a Deep Net to perform 3D volumetric delineation giv ...

ELSEVIER2020

FEM Based Statistical Data-Driven Modeling Approach for MFT Design Optimization

Drazen Dujic, Marko Mogorovic

This paper proposes a novel class of neural-network inspired statistical data-driven models, especially derived for the purpose of design optimization of medium frequency transformers. These models allow for an efficient (3-5 orders of magnitude faster com ...

2020

Square Attack: a query-efficient black-box adversarial attack via random search

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

We propose the Square Attack, a new score-based black-box

l_2

and

l_\infty

adversarial attack that does not rely on local gradient information and thus is not affected by gradient masking. The Square Attack is based on a randomized search scheme where ...

2020

Shape Reconstruction by Learning Differentiable Surface Representations

Pascal Fua, Mathieu Salzmann, Shaifali Parashar, Jan Bednarík, Erhan Gündogdu

Generative models that produce point clouds have emerged as a powerful tool to represent 3D surfaces, and the best current ones rely on learning an ensemble of parametric representations. Unfortunately, they offer no control over the deformations of the su ...

2020

Partially-supervised Mention Detection

James Henderson

Learning to detect entity mentions without using syntactic information can be useful for integration and joint optimization with other tasks. However, it is common to have partially annotated data for this problem. Here, we investigate two approaches to de ...

ACL2020

HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset

Boi Faltings, Diego Matteo Antognini

Today, recommender systems are an inevitable part of everyone's daily digital routine and are present on most internet platforms. State-of-the-art deep learning-based models require a large number of data to achieve their best performance. Many datasets fu ...

EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA2020

A geometry-inspired decision-based attack

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Yujia Liu

Deep neural networks have recently achieved tremen-dous success in image classification. Recent studies havehowever shown that they are easily misled into incorrectclassification decisions by adversarial examples. Adver-saries can even craft attacks by que ...

2019

Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism

Qian Wang, Jan Sickmann Hesthaven, Nicolò Ripamonti

Closure modeling based on the Mori-Zwanzig formalism has proven effective to improve the stability and accuracy of projection-based model order reduction. However, closure models are often expensive and infeasible for complex nonlinear systems. Towards eff ...

2019

Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments

Open-ended learning environments (OELEs) allow students to freely interact with the content and to discover important principles and concepts of the learning domain on their own. However, only some students possess the necessary skills for efficient and ef ...

International Educational Data Mining Society2019

SparseFool: a few pixels make a big difference

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Apostolos Modas

Deep Neural Networks have achieved extraordinary results on image classification tasks, but have been shown to be vulnerable to attacks with carefully crafted perturbations of the input data. Although most attacks usually change values of many image's pixe ...

IEEE2019

Essays in Empirical Asset Pricing

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Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

FEM Based Statistical Data-Driven Modeling Approach for MFT Design Optimization

Square Attack: a query-efficient black-box adversarial attack via random search

Shape Reconstruction by Learning Differentiable Surface Representations

Partially-supervised Mention Detection

HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset

A geometry-inspired decision-based attack

Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism

Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments

SparseFool: a few pixels make a big difference

Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

FEM Based Statistical Data-Driven Modeling Approach for MFT Design Optimization

Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments

Square Attack: a query-efficient black-box adversarial attack via random search

Shape Reconstruction by Learning Differentiable Surface Representations

Partially-supervised Mention Detection

HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset

SparseFool: a few pixels make a big difference

A geometry-inspired decision-based attack

Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism