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Regularization Techniques for Low-Resource Machine Translation

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Large Steps in Inverse Rendering of Geometry

Wenzel Alban Jakob, Baptiste Alexandre Marie Philippe Claude Nicolet

Inverse reconstruction from images is a central problem in many scientific and engineering disciplines. Recent progress on differentiable rendering has led to methods that can efficiently differentiate the full process of image formation with respect to mi ...

ASSOC COMPUTING MACHINERY2021

Disparity Between Batches as a Signal for Early Stopping

Patrick Thiran, Mahsa Forouzesh

We propose a metric for evaluating the generalization ability of deep neural networks trained with mini-batch gradient descent. Our metric, called gradient disparity, is the l2 norm distance between the gradient vectors of two mini-batches drawn from the t ...

Springer2021

Loss landscape and symmetries in Neural Networks

Mario Geiger

Neural networks (NNs) have been very successful in a variety of tasks ranging from machine translation to image classification. Despite their success, the reasons for their performance are still not well-understood. This thesis explores two main themes: lo ...

EPFL2021

Advances In Morphological Neural Networks: Training, Pruning And Enforcing Shape Constraints

Nikolaos Dimitriadis

In this paper, we study an emerging class of neural networks, the Morphological Neural networks, from some modern perspectives. Our approach utilizes ideas from tropical geometry and mathematical morphology. First, we state the training of a binary morphol ...

IEEE2021

Wasserstein Adversarial Regularization for learning with label noise

Devis Tuia, Sylvain Lobry, Nicolas Courty

Noisy labels often occur in vision datasets, especially when they are obtained from crowdsourcing or Web scraping. We propose a new regularization method, which enables learning robust classifiers in presence of noisy data. To achieve this goal, we propose ...

2021

OdiEnCorp 2.0: Odia-English Parallel Corpus for Machine Translation

Petr Motlicek

The preparation of parallel corpora is a challenging task, particularly for languages that suffer from under-representation in the digital world. In a multi-lingual country like India, the need for such parallel corpora is stringent for several low-resourc ...

European Language Resources Association (ELRA)2020

Sarah Kenderdine + Merete Sanderhoff

This conversation focuses on the work of Sarah Kenderdine and Merete Sanderhoff, both of whom are based in Europe working on and within museums, as well as playing leadership roles in pan-institutional organisations such as Europeana and the Australasian A ...

Routledge2020

Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization

Florent Gérard Krzakala, Lenka Zdeborová

We consider a commonly studied supervised classification of a synthetic dataset whose labels are generated by feeding a one-layer non-linear neural network with random iid inputs. We study the generalization performances of standard classifiers in the high ...

Curran Associates, Inc.2020

Notes on functions of hyperbolic type

Nicolas Monod

Functions of hyperbolic type encode representations on real or complex hyperbolic spaces, usually infinite-dimensional. These notes set up the complex case. As applications, we prove the existence of a non-trivial deformation family of representations of S ...

BELGIAN MATHEMATICAL SOC TRIOMPHE2020

A system for planning and/or providing neuromodulation

Grégoire Courtine, Vincent Delattre, Marco Capogrosso, Fabien Bertrand Paul Wagner, Karen Minassian

The present invention relates to a system for planning and/or providing neuromodulation (10), especially neurostimulation, comprising: - first data input module (26) for stimulation related basic data, - a stimulation related basic data storage module (28) ...

2019