Faculty
Since December 1st 2021 Dr. Sebastian Stich is a tenure track faculty at CISPA. Since June 2020 he is a member of the European Lab for Learning and Intelligent Systems. From December 1st 2016 to November 30th 2021, he worked as a research scientist at EPFL, hosted by Prof. Martin Jaggi, Machine Learning and Optimization Laboratory (MLO). From November 1st 2014 to October 31st 2016, he worked with Prof. Yurii Nesterov and Prof. François Glineur at the Center for Operations Research and Econometrics (CORE) and the ICTEAM. From September 15th 2010 to September 30th 2014, he was a PHD student in Prof. Emo Welzl's research group, supervised by Prof. Bernd Gärtner and Christian Lorenz Müller. And from September 2005 to March 2010 he did his Bachelor and Master in Mathematics at ETH Zurich.
Bayesian Deep Learning Workshop (BDL)
IEEE International Conference on Computer Vision (ICCV)
Semantic Perturbations with Normalizing Flows for Improved Generalization
International Conference on Machine Learning (ICML)
Consensus Control for Decentralized Deep Learning.
International Conference on Artificial Intelligence and Statistics (AISTATS)
LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads.
International Conference on Artificial Intelligence and Statistics (AISTATS)
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!
International Conference on Machine Learning (ICML)
Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data.
International Conference on Artificial Intelligence and Statistics (AISTATS)
Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates.
International Conference on Machine Learning (ICML)
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning.
International Conference on Machine Learning (ICML)
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates.
International Conference on Machine Learning (ICML)
Extrapolation for Large-batch Training in Deep Learning.