Zobrazeno 31 - 40
of 2 167
pro vyhledávání: '"Fischer, Marc"'
Autor:
Besta, Maciej, Fischer, Marc, Ben-Nun, Tal, Stanojevic, Dimitri, Licht, Johannes De Fine, Hoefler, Torsten
Publikováno v:
Proceedings of the ACM Transactions on Reconfigurable Technology and Systems (TRETS), 2020. Proceedings of the 27th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA), 2019
Developing high-performance and energy-efficient algorithms for maximum matchings is becoming increasingly important in social network analysis, computational sciences, scheduling, and others. In this work, we propose the first maximum matching algor
Externí odkaz:
http://arxiv.org/abs/2010.14684
Autor:
Küstner, Thomas, Hepp, Tobias, Fischer, Marc, Schwartz, Martin, Fritsche, Andreas, Häring, Hans-Ulrich, Nikolaou, Konstantin, Bamberg, Fabian, Yang, Bin, Schick, Fritz, Gatidis, Sergios, Machann, Jürgen
Purpose: To enable fast and reliable assessment of subcutaneous and visceral adipose tissue compartments derived from whole-body MRI. Methods: Quantification and localization of different adipose tissue compartments from whole-body MR images is of hi
Externí odkaz:
http://arxiv.org/abs/2008.02251
We extend randomized smoothing to cover parameterized transformations (e.g., rotations, translations) and certify robustness in the parameter space (e.g., rotation angle). This is particularly challenging as interpolation and rounding effects mean th
Externí odkaz:
http://arxiv.org/abs/2002.12463
Fair representation learning provides an effective way of enforcing fairness constraints without compromising utility for downstream users. A desirable family of such fairness constraints, each requiring similar treatment for similar individuals, is
Externí odkaz:
http://arxiv.org/abs/2002.10312
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems (TPDS), 2022
Graph processing has become an important part of various areas of computing, including machine learning, medical applications, social network analysis, computational sciences, and others. A growing amount of the associated graph processing workloads
Externí odkaz:
http://arxiv.org/abs/1912.12740
In deep reinforcement learning (RL), adversarial attacks can trick an agent into unwanted states and disrupt training. We propose a system called Robust Student-DQN (RS-DQN), which permits online robustness training alongside Q networks, while preser
Externí odkaz:
http://arxiv.org/abs/1911.00887
Autor:
Besta, Maciej, Gerstenberger, Robert, Peter, Emanuel, Fischer, Marc, Podstawski, Michał, Barthels, Claude, Alonso, Gustavo, Hoefler, Torsten
Graph processing has become an important part of multiple areas of computer science, such as machine learning, computational sciences, medical applications, social network analysis, and many others. Numerous graphs such as web or social networks may
Externí odkaz:
http://arxiv.org/abs/1910.09017
Publikováno v:
In Anesthésie & Réanimation September 2023 9(4):366-375
Publikováno v:
In Anesthésie & Réanimation September 2023 9(4):376-381
Autor:
Chiari, Pascal *, Desebbe, Olivier, Durand, Michel, Fischer, Marc-Olivier, Lena-Quintard, Diane, Palao, Jean-Charles, Samson, Géraldine, Varillon, Yvonne, Vaz, Bernadette, Joseph, Pierre *, Ferraris, Arnaud *, Jacquet-Lagreze, Matthias *, Pozzi, Matteo, Maucort-Boulch, Delphine, Ovize, Michel, Bidaux, Gabriel, Mewton, Nathan, Fellahi, Jean-Luc *
Publikováno v:
In Journal of Cardiothoracic and Vascular Anesthesia August 2023 37(8):1368-1376