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ORCIDMathieu Sinn
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2020 – today
- 2022
[c24]Stefano Braghin
, Marco Simioni, Mathieu Sinn:
DLPFS: The Data Leakage Prevention FileSystem. ACNS Workshops 2022: 380-397- [c23]Ambrish Rawat, Killian Levacher, Mathieu Sinn:
The Devil Is in the GAN: Backdoor Attacks and Defenses in Deep Generative Models. ESORICS (3) 2022: 776-783 - [i16]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 abs/2202.12443 (2022) - 2021
- [c22]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: 125-138 - [i15]Ambrish Rawat, Killian Levacher, Mathieu Sinn:
The Devil is in the GAN: Defending Deep Generative Models Against Backdoor Attacks. CoRR abs/2108.01644 (2021) - [i14]Stefano Braghin, Marco Simioni, Mathieu Sinn:
DLPFS: The Data Leakage Prevention FileSystem. CoRR abs/2108.13785 (2021) - [i13]Ambrish Rawat, Mathieu Sinn, Beat Buesser:
Automated Robustness with Adversarial Training as a Post-Processing Step. CoRR abs/2109.02532 (2021) - [i12]Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Sergio Maffeis, Chris Hankin:
Certified Federated Adversarial Training. CoRR abs/2112.10525 (2021) - 2020
- [i11]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 abs/2007.10987 (2020) - [i10]Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Beat Buesser:
FAT: Federated Adversarial Training. CoRR abs/2012.01791 (2020)
2010 – 2019
- 2019
- [e1]Carlos Alzate, Anna Monreale, Haytham Assem, Albert Bifet, Teodora Sandra Buda, Bora Caglayan, Brett Drury, Eva García-Martín, Ricard Gavaldà, Stefan Kramer, Niklas Lavesson, Michael Madden, Ian M. Molloy, Maria-Irina Nicolae, Mathieu Sinn:
ECML PKDD 2018 Workshops - Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings. Lecture Notes in Computer Science 11329, Springer 2019, ISBN 978-3-030-13452-5 [contents] - [i9]Evelyn Duesterwald, Anupama Murthi, Ganesh Venkataraman, Mathieu Sinn, Deepak Vijaykeerthy:
Exploring the Hyperparameter Landscape of Adversarial Robustness. CoRR abs/1905.03837 (2019) - 2018
- [c21]Mathieu Sinn, Ambrish Rawat:
Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training. AISTATS 2018: 642-651 - [c20]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: 1487-1492 - [i8]Hoang Thanh Lam, Tran Ngoc Minh, Mathieu Sinn, Beat Buesser, Martin Wistuba:
Learning Features For Relational Data. CoRR abs/1801.05372 (2018) - [i7]Han Qiu, Hoang Thanh Lam, Francesco Fusco, Mathieu Sinn:
Learning Correlation Space for Time Series. CoRR abs/1802.03628 (2018) - [i6]Tran Ngoc Minh, Mathieu Sinn, Hoang Thanh Lam, Martin Wistuba:
Automated Image Data Preprocessing with Deep Reinforcement Learning. CoRR abs/1806.05886 (2018) - [i5]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 abs/1807.01069 (2018) - 2017
- [j6]Alhussein Fawzi, Mathieu Sinn, Pascal Frossard:
Multitask Additive Models With Shared Transfer Functions Based on Dictionary Learning. IEEE Trans. Signal Process. 65(5): 1352-1365 (2017) - [c19]Magnus Mossberg, Mathieu Sinn:
Cross-correlations of zero crossings in jointly Gaussian and stationary processes with zero means. ICASSP 2017: 4286-4290 - [i4]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 abs/1706.00327 (2017) - 2016
- [j5]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) - [j4]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) - [j3]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): 1589-1601 (2016) - [c18]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 - 2015
- [c17]Tri Kurniawan Wijaya, Mathieu Sinn, Bei Chen:
Forecasting Uncertainty in Electricity Demand. AAAI Workshop: Computational Sustainability 2015 - [i3]Alhussein Fawzi, Mathieu Sinn, Pascal Frossard:
Multi-task additive models with shared transfer functions based on dictionary learning. CoRR abs/1505.04966 (2015) - 2014
- [c16]Mathieu Sinn:
Energy demand forecasting: industry practices and challenges. e-Energy 2014: 121 - [c15]Bei Chen, Mathieu Sinn, Joern Ploennigs, Anika Schumann:
Statistical Anomaly Detection in Mean and Variation of Energy Consumption. ICPR 2014: 3570-3575 - 2013
- [j2]Johannes Textor, Mathieu Sinn, Rob J. De Boer:
Analytical results on the Beauchemin model of lymphocyte migration. BMC Bioinform. 14(S-6): S10 (2013) - [c14]Mathieu Sinn, Bei Chen:
Central Limit Theorems for Conditional Markov Chains. AISTATS 2013: 554-562 - [c13]Arieh Schlote, Bei Chen, Mathieu Sinn, Robert Shorten:
The effect of feedback in the assignment problem in shared bicycle systems. ICCVE 2013: 960-961 - [c12]Carlos Alzate, Mathieu Sinn:
Improved Electricity Load Forecasting via Kernel Spectral Clustering of Smart Meters. ICDM 2013: 943-948 - [c11]Francesco Fusco, Mathieu Sinn:
Integrated state estimation and load modelling for distribution grids with ampere measurements. ISGT Europe 2013: 1-5 - [c10]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: 53-58 - 2012
- [c9]Mathieu Sinn, Ji Won Yoon, Francesco Calabrese, Eric Bouillet:
Predicting arrival times of buses using real-time GPS measurements. ITSC 2012: 1227-1232 - [c8]Mathieu Sinn, Bei Chen:
Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions. NIPS 2012: 1817-1825 - [c7]Amadou Ba, Mathieu Sinn, Yannig Goude, Pascal Pompey:
Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting. NIPS 2012: 2519-2527 - [c6]Mathieu Sinn, Ali Ghodsi, Karsten Keller:
Detecting Change-Points in Time Series by Maximum Mean Discrepancy of Ordinal Pattern Distributions. UAI 2012: 786-794 - [i2]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 abs/1203.3500 (2012) - [i1]Mathieu Sinn, Ali Ghodsi, Karsten Keller:
Detecting Change-Points in Time Series by Maximum Mean Discrepancy of Ordinal Pattern Distributions. CoRR abs/1210.4903 (2012) - 2011
- [j1]Mathieu Sinn, Karsten Keller:
Estimation of ordinal pattern probabilities in Gaussian processes with stationary increments. Comput. Stat. Data Anal. 55(4): 1781-1790 (2011) - [c5]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 - [c4]Mathieu Sinn, Pascal Poupart:
Smart walkers!: enhancing the mobility of the elderly. AAMAS 2011: 1133-1134 - [c3]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: 1-6 - [c2]Mathieu Sinn, Pascal Poupart:
Asymptotic Theory for Linear-Chain Conditional Random Fields. AISTATS 2011: 679-687 - 2010
- [c1]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: 392-400
Coauthor Index
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