254 citations · 344 across the 8 of their papers we have counts for
8 papers
Constrained deep neural network architecture search for IoT devices accounting hardware calibration
Florian Scheidegger, Luca Benini, Costas Bekas +1
Deep neural networks achieve outstanding results in challenging image classification tasks. However, the design of network topologies is a complex task and the research community m…
NeuNetS: An Automated Synthesis Engine for Neural Network Design
Atin Sood, Benjamin Elder, Benjamin Herta +17
Application of neural networks to a vast variety of practical applications is transforming the way AI is applied in practice. Pre-trained neural network models available through AP…
TAPAS: Train-less Accuracy Predictor for Architecture Search
R. Istrate, F. Scheidegger, G. Mariani +3
In recent years an increasing number of researchers and practitioners have been suggesting algorithms for large-scale neural network architecture search: genetic algorithms, reinfo…
Corpus Conversion Service: A Machine Learning Platform to Ingest Documents at Scale
Peter W J Staar, Michele Dolfi, Christoph Auer +1
Over the past few decades, the amount of scientific articles and technical literature has increased exponentially in size. Consequently, there is a great need for systems that can…
Corpus Conversion Service: A machine learning platform to ingest documents at scale [Poster abstract]
Peter W J Staar, Michele Dolfi, Christoph Auer +1
Over the past few decades, the amount of scientific articles and technical literature has increased exponentially in size. Consequently, there is a great need for systems that can…
Incremental Training of Deep Convolutional Neural Networks
Roxana Istrate, Adelmo Cristiano Innocenza Malossi, Costas Bekas +1
We propose an incremental training method that partitions the original network into sub-networks, which are then gradually incorporated in the running network during the training p…
BAGAN: Data Augmentation with Balancing GAN
Giovanni Mariani, Florian Scheidegger, Roxana Istrate +2
Image classification datasets are often imbalanced, characteristic that negatively affects the accuracy of deep-learning classifiers. In this work we propose balancing GAN (BAGAN)…
Challenges and Recommendations for Preparing HPC Applications for Exascale
Erika Abraham, Costas Bekas, Ivona Brandic +5
While the HPC community is working towards the development of the first Exaflop computer (expected around 2020), after reaching the Petaflop milestone in 2008 still only few HPC ap…