Arturo Marban | DeepAI

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∙ 12/01/2020

Communication-Efficient Federated Distillation

Communication constraints are one of the major challenges preventing the...

0 Felix Sattler, et al. ∙

∙ 04/02/2020

Learning Sparse Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T)

Deep neural networks (DNN) have shown remarkable success in a variety of...

0 Arturo Marban, et al. ∙

∙ 07/27/2019

DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks

The field of video compression has developed some of the most sophistica...

0 Simon Wiedemann, et al. ∙

∙ 05/15/2019

DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression

We present DeepCABAC, a novel context-adaptive binary arithmetic coder f...

0 Simon Wiedemann, et al. ∙

∙ 12/18/2018

Entropy-Constrained Training of Deep Neural Networks

We propose a general framework for neural network compression that is mo...

0 Simon Wiedemann, et al. ∙

∙ 05/30/2018

Counterstrike: Defending Deep Learning Architectures Against Adversarial Samples by Langevin Dynamics with Supervised Denoising Autoencoder

Adversarial attacks on deep learning models have been demonstrated to be...

2 Vignesh Srinivasan, et al. ∙

∙ 05/22/2018

A Recurrent Convolutional Neural Network Approach for Sensorless Force Estimation in Robotic Surgery

Providing force feedback as relevant information in current Robot-Assist...

0 Arturo Marban, et al. ∙

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