Mathieu Sinn | DeepAI

AI Chat

Featured Co-authors

Pascal Frossard
121 publications
Yi Zhou
114 publications
Pascal Poupart
56 publications
Mikhail Yurochkin
43 publications
Bei Chen
39 publications
Minh-Ngoc Tran
32 publications
Han Qiu
27 publications
Martin Wistuba
23 publications
Ali Anwar
23 publications
Mayank Agarwal
19 publications
Alhussein Fawzi
17 publications

∙ 02/25/2022

Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach

Federated Learning (FL) is a novel paradigm for the shared training of m...

4 Nathalie Baracaldo, et al. ∙

∙ 12/20/2021

Certified Federated Adversarial Training

In federated learning (FL), robust aggregation schemes have been develop...

0 Giulio Zizzo, et al. ∙

∙ 09/06/2021

Automated Robustness with Adversarial Training as a Post-Processing Step

Adversarial training is a computationally expensive task and hence searc...

0 Ambrish Rawat, et al. ∙

∙ 08/31/2021

DLPFS: The Data Leakage Prevention FileSystem

Shared folders are still a common practice for granting third parties ac...

0 Stefano Braghin, et al. ∙

∙ 08/03/2021

The Devil is in the GAN: Defending Deep Generative Models Against Backdoor Attacks

Deep Generative Models (DGMs) allow users to synthesize data from comple...

30 Ambrish Rawat, et al. ∙

∙ 12/03/2020

FAT: Federated Adversarial Training

Federated learning (FL) is one of the most important paradigms addressin...

0 Giulio Zizzo, et al. ∙

∙ 07/22/2020

IBM Federated Learning: an Enterprise Framework White Paper V0.1

Federated Learning (FL) is an approach to conduct machine learning witho...

0 Heiko Ludwig, et al. ∙

∙ 05/09/2019

Exploring the Hyperparameter Landscape of Adversarial Robustness

Adversarial training shows promise as an approach for training models th...

0 Evelyn Duesterwald, et al. ∙

∙ 11/20/2018

Castor: Contextual IoT Time Series Data and Model Management at Scale

We demonstrate Castor, a cloud-based system for contextual IoT time seri...

0 Bei Chen, et al. ∙

∙ 07/03/2018

Adversarial Robustness Toolbox v0.2.2

Adversarial examples have become an indisputable threat to the security ...

0 Maria-Irina Nicolae, et al. ∙

∙ 06/15/2018

Automated Image Data Preprocessing with Deep Reinforcement Learning

Data preparation, i.e. the process of transforming raw data into a forma...

2 Tran Ngoc Minh, et al. ∙

∙ 02/10/2018

Learning Correlation Space for Time Series

We propose an approximation algorithm for efficient correlation search i...

0 Han Qiu, et al. ∙

∙ 01/16/2018

Learning Features For Relational Data

Feature engineering is one of the most important but tedious tasks in da...

0 Hoang Thanh Lam, et al. ∙

∙ 06/01/2017

One button machine for automating feature engineering in relational databases

Feature engineering is one of the most important and time consuming task...

0 Hoang Thanh Lam, et al. ∙

∙ 05/25/2017

Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training

Generative Adversarial Networks (GANs) have become a widely popular fram...

0 Mathieu Sinn, et al. ∙

∙ 05/19/2015

Multi-task additive models with shared transfer functions based on dictionary learning

Additive models form a widely popular class of regression models which r...

0 Alhussein Fawzi, et al. ∙

∙ 03/15/2012

Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker

Rollating walkers are popular mobility aids used by older adults to impr...

0 Farheen Omar, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world