Mathieu Sinn

Publication Activity (10 Years)

Years Active: 2010-2022
Publications (10 Years): 24

Top Topics

Dictionary Learning

Data Leakage Prevention

Demand Forecasting

Top Venues

IBM J. Res. Dev.

Publications

Stefano Braghin, Marco Simioni, Mathieu Sinn
DLPFS: The Data Leakage Prevention FileSystem. ACNS Workshops (2022)
Ambrish Rawat, Killian Levacher, Mathieu Sinn
The Devil Is in the GAN: Backdoor Attacks and Defenses in Deep Generative Models. ESORICS (3) (2022)
Nathalie Baracaldo, Ali Anwar, Mark Purcell, Ambrish Rawat, Mathieu Sinn, Bashar Altakrouri, Dian Balta, Mahdi Sellami, Peter Kuhn, Ulrich Schöpp, Matthias Buchinger
Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach. CoRR (2022)
Ambrish Rawat, Mathieu Sinn, Beat Buesser
Automated Robustness with Adversarial Training as a Post-Processing Step. CoRR (2021)
Ambrish Rawat, Killian Levacher, Mathieu Sinn
The Devil is in the GAN: Defending Deep Generative Models Against Backdoor Attacks. CoRR (2021)
Dian Balta, Mahdi Sellami, Peter Kuhn, Ulrich Schöpp, Matthias Buchinger, Nathalie Baracaldo, Ali Anwar, Heiko Ludwig, Mathieu Sinn, Mark Purcell, Bashar Altakrouri
Accountable Federated Machine Learning in Government: Engineering and Management Insights. ePart (2021)
Stefano Braghin, Marco Simioni, Mathieu Sinn
DLPFS: The Data Leakage Prevention FileSystem. CoRR (2021)
Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Sergio Maffeis, Chris Hankin
Certified Federated Adversarial Training. CoRR (2021)
Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Jeremy Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, Mark Purcell, Ambrish Rawat, Tran Ngoc Minh, Naoise Holohan, Supriyo Chakraborty, Shalisha Witherspoon, Dean Steuer, Laura Wynter, Hifaz Hassan, Sean Laguna, Mikhail Yurochkin, Mayank Agarwal, Ebube Chuba, Annie Abay
IBM Federated Learning: an Enterprise Framework White Paper V0.1. CoRR (2020)
Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Beat Buesser
FAT: Federated Adversarial Training. CoRR (2020)
Evelyn Duesterwald, Anupama Murthi, Ganesh Venkataraman, Mathieu Sinn, Deepak Vijaykeerthy
Exploring the Hyperparameter Landscape of Adversarial Robustness. CoRR (2019)
Hoang Thanh Lam, Tran Ngoc Minh, Mathieu Sinn, Beat Buesser, Martin Wistuba
Learning Features For Relational Data. CoRR (2018)
Maria-Irina Nicolae, Mathieu Sinn, Tran Ngoc Minh, Ambrish Rawat, Martin Wistuba, Valentina Zantedeschi, Ian M. Molloy, Benjamin Edwards
Adversarial Robustness Toolbox v0.2.2. CoRR (2018)
Mathieu Sinn, Ambrish Rawat
Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training. AISTATS (2018)
Bei Chen, Bradley Eck, Francesco Fusco, Robert Gormally, Mark Purcell, Mathieu Sinn, Seshu Tirupathi
Castor: Contextual IoT Time Series Data and Model Management at Scale. ICDM Workshops (2018)
Tran Ngoc Minh, Mathieu Sinn, Hoang Thanh Lam, Martin Wistuba
Automated Image Data Preprocessing with Deep Reinforcement Learning. CoRR (2018)
Han Qiu, Hoang Thanh Lam, Francesco Fusco, Mathieu Sinn
Learning Correlation Space for Time Series. CoRR (2018)
Magnus Mossberg, Mathieu Sinn
Cross-correlations of zero crossings in jointly Gaussian and stationary processes with zero means. ICASSP (2017)
Alhussein Fawzi, Mathieu Sinn, Pascal Frossard
Multitask Additive Models With Shared Transfer Functions Based on Dictionary Learning. IEEE Trans. Signal Process. 65 (5) (2017)
Hoang Thanh Lam, Johann-Michael Thiebaut, Mathieu Sinn, Bei Chen, Tiep Mai, Oznur Alkan
One button machine for automating feature engineering in relational databases. CoRR (2017)
Lloyd A. Treinish, James P. Cipriani, Anthony Praino, Amith Singhee, H. Wang, Mathieu Sinn, Vincent P. A. Lonij, Jean-Baptiste Fiot, B. Chen
Enabling coupled models to predict the business impact of weather on electric utilities. IBM J. Res. Dev. 60 (1) (2016)
Francesco Fusco, Ulrike Fischer, Vincent P. A. Lonij, Pascal Pompey, Jean-Baptiste Fiot, Bei Chen, Yiannis Gkoufas, Mathieu Sinn
Data Management System for Energy Analytics and its Application to Forecasting. EDBT/ICDT Workshops (2016)
Alhussein Fawzi, Jean-Baptiste Fiot, Bei Chen, Mathieu Sinn, Pascal Frossard
Structured Dimensionality Reduction for Additive Model Regression. IEEE Trans. Knowl. Data Eng. 28 (6) (2016)
Kevin Warren, Ron F. Ambrosio, Bei Chen, Yuhui Fu, Soumyadip Ghosh, Dzung T. Phan, Mathieu Sinn, Chunhua Tian, Chandu Visweswariah
Managing uncertainty in electricity generation and demand forecasting. IBM J. Res. Dev. 60 (1) (2016)
Tri Kurniawan Wijaya, Mathieu Sinn, Bei Chen
Forecasting Uncertainty in Electricity Demand. AAAI Workshop: Computational Sustainability (2015)
Alhussein Fawzi, Mathieu Sinn, Pascal Frossard
Multi-task additive models with shared transfer functions based on dictionary learning. CoRR (2015)
Mathieu Sinn
Energy demand forecasting: industry practices and challenges. e-Energy (2014)
Bei Chen, Mathieu Sinn, Joern Ploennigs, Anika Schumann
Statistical Anomaly Detection in Mean and Variation of Energy Consumption. ICPR (2014)
Carlos Alzate, Mathieu Sinn
Improved Electricity Load Forecasting via Kernel Spectral Clustering of Smart Meters. ICDM (2013)
Mathieu Sinn, Bei Chen
Central Limit Theorems for Conditional Markov Chains. AISTATS (2013)
Arieh Schlote, Bei Chen, Mathieu Sinn, Robert Shorten
The effect of feedback in the assignment problem in shared bicycle systems. ICCVE (2013)
Bei Chen, Fabio Pinelli, Mathieu Sinn, Adi Botea, Francesco Calabrese
Uncertainty in urban mobility: Predicting waiting times for shared bicycles and parking lots. ITSC (2013)
Francesco Fusco, Mathieu Sinn
Integrated state estimation and load modelling for distribution grids with ampere measurements. ISGT Europe (2013)
Johannes Textor, Mathieu Sinn, Rob J. De Boer
Analytical results on the Beauchemin model of lymphocyte migration. BMC Bioinform. 14 (S-6) (2013)
Farheen Omar, Mathieu Sinn, Jakub Truszkowski, Pascal Poupart, James Yungjen Tung, Allen Caine
Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker CoRR (2012)
Mathieu Sinn, Ali Ghodsi, Karsten Keller
Detecting Change-Points in Time Series by Maximum Mean Discrepancy of Ordinal Pattern Distributions CoRR (2012)
Mathieu Sinn, Ji Won Yoon, Francesco Calabrese, Eric Bouillet
Predicting arrival times of buses using real-time GPS measurements. ITSC (2012)
Amadou Ba, Mathieu Sinn, Yannig Goude, Pascal Pompey
Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting. NIPS (2012)
Mathieu Sinn, Ali Ghodsi, Karsten Keller
Detecting Change-Points in Time Series by Maximum Mean Discrepancy of Ordinal Pattern Distributions. UAI (2012)
Mathieu Sinn, Bei Chen
Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions. NIPS (2012)
Mathieu Sinn, Pascal Poupart
Smart walkers!: enhancing the mobility of the elderly. AAMAS (2011)
Mathieu Sinn, Pascal Poupart
Error Bounds for Online Predictions of Linear-Chain Conditional Random Fields: Application to Activity Recognition for Users of Rolling Walkers. ICMLA (2) (2011)
James Yungjen Tung, Jonathan F. L. Semple, Wei X. Woo, Wei-Shou Hsu, Mathieu Sinn, Eric A. Roy, Pascal Poupart
Ambulatory Assessment of Lifestyle Factors for Alzheimer's Disease and Related Dementias. AAAI Spring Symposium: Computational Physiology (2011)
Mathieu Sinn, Pascal Poupart
Asymptotic Theory for Linear-Chain Conditional Random Fields. AISTATS (2011)
Mathieu Sinn, Karsten Keller
Estimation of ordinal pattern probabilities in Gaussian processes with stationary increments. Comput. Stat. Data Anal. 55 (4) (2011)
Farheen Omar, Mathieu Sinn, Jakub Truszkowski, Pascal Poupart, James Yungjen Tung, Allen Caine
Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker. UAI (2010)