Celestine Mendler-Dünner
Celestine Mendler-Dünner
Max Planck Institute for Intelligent Systems
Verified email at tuebingen.mpg.de - Homepage
Cited by
Cited by
Scalable and interpretable product recommendations via overlapping co-clustering
R Heckel, M Vlachos, T Parnell, C Dünner
ICDE 2017 - IEEE 33rd International Conference on Data Engineering, 1033-1044, 2017
Performative prediction
JC Perdomo*, T Zrnic*, C Mendler-Dünner, M Hardt
ICML 2020 - International Conference on Machine Learning, 2020
Primal-dual rates and certificates
C Dünner, S Forte, M Takáč, M Jaggi
ICML 2016 - Proceedings of The 33rd International Conference on Machine Learning, 2016
Computer algorithms for three-dimensional measurement of humeral anatomy: analysis of 140 paired humeri
L Vlachopoulos, C Dünner, T Gass, M Graf, O Goksel, C Gerber, ...
JSES 2016 - Journal of shoulder and elbow surgery 25, 2016
A Distributed Second-Order Algorithm You Can Trust
C Dünner, A Lucchi, M Gargiani, A Bian, T Hofmann, M Jaggi
ICML 2018 - International Conference on Machine Learning, Stockholm, 2018
Snap ML: A hierarchical framework for machine learning
C Dünner, T Parnell, D Sarigiannis, N Ioannou, A Anghel, G Ravi, ...
NeurIPS 2018 - Advances in Neural Information Processing Systems, 250-260, 2018
Addressing interpretability and cold-start in matrix factorization for recommender systems
M Vlachos*, C Dünner*, R Heckel, VG Vassiliadis, T Parnell, K Atasu
TKDE - IEEE Transactions on Knowledge and Data Engineering 31 (7), 1253-1266, 2018
Large-Scale Stochastic Learning using GPUs
T Parnell, C Dünner, K Atasu, M Sifalakis, H Pozidis
ParLearning 2017 - Proceedings of the 6th International Workshop on Parallel …, 2017
Stochastic Optimization for Performative Prediction
C Mendler-Dünner, J Perdomo, T Zrnic, M Hardt
NeurIPS 2020 - Advances in Neural Information Processing Systems 33, 2020
Understanding and Optimizing the Performance of Distributed Machine Learning Applications on Apache Spark
C Dünner, T Parnell, K Atasu, M Sifalakis, H Pozidis
IEEE Big Data 2017 - IEEE International Conference on Big Data, 2017
Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems
C Dünner, T Parnell, M Jaggi
NIPS 2017 - Advances in Neural Information Processing Systems, 4261-4270, 2017
Linear-Complexity Relaxed Word Mover's Distance with GPU Acceleration
K Atasu, T Parnell, C Dünner, M Sifalakis, H Pozidis, V Vasileiadis, ...
IEEE Big Data 2017 - IEEE International Conference on Big Data, 2017
Tera-scale coordinate descent on GPUs
T Parnell, C Dünner, K Atasu, M Sifalakis, H Pozidis
FGCS - Future Generation Computer Systems 108, 1173-1191, 2020
Sampling acquisition functions for batch Bayesian optimization
A De Palma, C Mendler-Dünner, T Parnell, A Anghel, H Pozidis
BNP@NeurIPS 2018 - Workshop on Bayesian Nonparametrics, 2019
Differentially Private Stochastic Coordinate Descent
G Damaskinos, C Mendler-Dünner, R Guerraoui, N Papandreou, ...
AAAI 2021 - Advancement of Artificial Intelligence, 2020
Revisiting Design Choices in Proximal Policy Optimization
C Ching-Yun Hsu, C Mendler-Dünner, M Hardt
RWRL@NeurIPS 2020 - Workshop on Real World Challenges in RL, 2020
SySCD: A System-Aware Parallel Coordinate Descent Algorithm
N Ioannou*, C Mendler-Dünner*, T Parnell
NeurIPS 2019 - Advances in Neural Information Processing Systems, 592-602, 2019
A novel method for the approximation of humeral head retrotorsion based on three-dimensional registration of the bicipital groove
L Vlachopoulos, F Carrillo, C Dünner, C Gerber, G Székely, P Fürnstahl
JBJS 100 (15), e101, 2018
Capacity of the MLC NAND Flash Channel
T Parnell, C Dünner, T Mittelholzer, N Papandreou
J-SAC - IEEE Journal on Selected Areas in Communications 34 (9), 2354-2365, 2016
Power control for cellular networks with large antenna arrays and ubiquitous relaying
RTL Rolny, C Dünner, A Wittneben
SPAWC 2014 - IEEE 15th International Workshop on Signal Processing Advances …, 2014
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