Concept

Neural machine translation

Publications associées (122)

dhSegment: A generic deep-learning approach for document segmentation

Frédéric Kaplan, Sofia Ares Oliveira, Benoît Laurent Auguste Seguin

In recent years there have been multiple successful attempts tackling document processing problems separately by designing task specific hand-tuned strategies. We argue that the diversity of historical document processing tasks prohibits to solve them one ...

IEEE2018

Not All Samples Are Created Equal: Deep Learning with Importance Sampling

François Fleuret, Angelos Katharopoulos

Deep neural network training spends most of the computation on examples that are properly handled, and could be ignored. We propose to mitigate this phenomenon with a principled importance sampling scheme that focuses computation on "informative" examples ...

Idiap2018

Sparsified SGD with Memory

Martin Jaggi, Sebastian Urban Stich, Jean-Baptiste Francis Marie Juliette Cordonnier

Huge scale machine learning problems are nowadays tackled by distributed optimization algorithms, i.e. algorithms that leverage the compute power of many devices for training. The communication overhead is a key bottleneck that hinders perfect scalability. ...

2018

Towards Commoditizing Simulations of System Models Using Recurrent Neural Networks

Ahmet Caner Yüzügüler

System modeling and simulation plays a crucial role in the engineering of large and complex systems from various fields, such as industrial automation or power systems. In this paper, we propose a method that can be used to easily deploy high fidelity simu ...

IEEE2018

Comparing human and machine performances in transcribing 18th century handwritten Venetian script

Frédéric Kaplan, Sofia Ares Oliveira

Automatic transcription of handwritten texts has made important progress in the recent years. This increase in performance, essentially due to new architectures combining convolutional neural networks with recurrent neutral networks, opens new avenues for ...

2018

Comparing human and machine performances in transcribing 18th century handwritten Venetian script

Sofia Ares Oliveira

2018

The SUMMA Platform Prototype

Hervé Bourlard, Philip Neil Garner, Andrei Popescu-Belis, Nikolaos Pappas, Sibo Tong, Yang Wang, Ahmed Ali, Steve Renals, Lesly Sadiht Miculicich Werlen, Marco Damonte, Hassan Sajjad

We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring. The platform contains a rich suite of low-level and high-level natural language processing technologies: automatic speech recognition of broadca ...

Association for Computational Linguistics2017

Matrix-binding checkpoint immunotherapies enhance antitumor efficacy and reduce adverse events

Jeffrey Alan Hubbell, Melody Swartz, Hans Mattias Larsson, Lambert Charles François Potin, Gabriele Galliverti, Jun Ishihara, Kazuto Fukunaga

Immune checkpoint blockade exhibits considerable antitumor activity, but previous studies have reported instances of severe treatment-related adverse events. We sought to explore local immune checkpoint blockade, with an antibody (Ab) form that would be re ...

Amer Assoc Advancement Science2017

Hybrid Neural Networks for Learning the Trend in Time Series

Karl Aberer, Tao Lin, Tian Guo

The trend of time series characterizes the intermediate upward and downward behaviour of time series. Learning and forecasting the trend in time series data play an important role in many real applications, ranging from resource allocation in data centers, ...

2017

An Investigation of Deep Neural Networks for Multilingual Speech Recognition Training and Adaptation

Hervé Bourlard, Philip Neil Garner, Sibo Tong

Different training and adaptation techniques for multilingual Automatic Speech Recognition (ASR) are explored in the context of hybrid systems, exploiting Deep Neural Networks (DNN) and Hidden Markov Models (HMM). In multilingual DNN training, the hidden l ...

2017

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