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Celestine Mendler-DŁnner
Celestine Mendler-DŁnner
Max Planck Institute for Intelligent Systems
Adres„ de e-mail confirmat„ pe tuebingen.mpg.de - Pagina de pornire
Titlu
Citat de
Citat de
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Performative prediction
JC Perdomo, T Zrnic, C Mendler-DŁnner, M Hardt
ICML 2020 - International Conference on Machine Learning, 2020
1642020
Scalable and interpretable product recommendations via overlapping co-clustering
R Heckel, M Vlachos, T Parnell, C DŁnner
ICDE 2017 - IEEE 33rd International Conference on Data Engineering, 1033-1044, 2017
712017
Primal-dual rates and certificates
C DŁnner, S Forte, M TakŠŤ, M Jaggi
ICML 2016 - Proceedings of The 33rd International Conference on Machine Learning, 2016
662016
Stochastic Optimization for Performative Prediction
C Mendler-DŁnner, J Perdomo, T Zrnic, M Hardt
NeurIPS 2020 - Advances in Neural Information Processing Systems 33, 2020
612020
Revisiting Design Choices in Proximal Policy Optimization
C Ching-Yun Hsu, C Mendler-DŁnner, M Hardt
RWRL@NeurIPS 2020 - Workshop on Real World Challenges in RL, 2020
40*2020
Computer algorithms for three-dimensional measurement of humeral anatomy: analysis of 140 paired humeri
L Vlachopoulos, C DŁnner, T Gass, M Graf, O Goksel, C Gerber, ...
JSES 2016 - Journal of shoulder and elbow surgery 25, 2016
362016
A Distributed Second-Order Algorithm You Can Trust
C DŁnner, A Lucchi, M Gargiani, A Bian, T Hofmann, M Jaggi
ICML 2018 - International Conference on Machine Learning, Stockholm, 2018
312018
Snap ML: A hierarchical framework for machine learning
C DŁnner, T Parnell, D Sarigiannis, N Ioannou, A Anghel, G Ravi, ...
NeurIPS 2018 - Advances in Neural Information Processing Systems, 250-260, 2018
30*2018
Alternative Microfoundations for Strategic Classification
M Jagadeesan, C Mendler-DŁnner, M Hardt
ICML 2021 - International Conference on Machine Learning, 4687-4697, 2021
272021
Addressing interpretability and cold-start in matrix factorization for recommender systems
M Vlachos*, C DŁnner*, R Heckel, VG Vassiliadis, T Parnell, K Atasu
TKDE - IEEE Transactions on Knowledge and Data Engineering 31 (7), 1253-1266, 2018
262018
Understanding and Optimizing the Performance of Distributed Machine Learning Applications on Apache Spark
C DŁnner, T Parnell, K Atasu, M Sifalakis, H Pozidis
IEEE Big Data 2017 - IEEE International Conference on Big Data, 2017
20*2017
Large-Scale Stochastic Learning using GPUs
T Parnell, C DŁnner, K Atasu, M Sifalakis, H Pozidis
ParLearning 2017 - Proceedings of the 6th International Workshop on Parallel†…, 2017
182017
Linear-Complexity Relaxed Word Mover's Distance with GPU Acceleration
K Atasu, T Parnell, C DŁnner, M Sifalakis, H Pozidis, V Vasileiadis, ...
IEEE Big Data 2017 - IEEE International Conference on Big Data, 2017
162017
Sampling acquisition functions for batch Bayesian optimization
A De Palma, C Mendler-DŁnner, T Parnell, A Anghel, H Pozidis
BNP@NeurIPS 2018 - Workshop on Bayesian Nonparametrics, 2019
152019
Regret Minimization with Performative Feedback
M Jagadeesan, T Zrnic, C Mendler-DŁnner
ICML 2022 - International Conference on Machine Learning 162, 9760--9785, 2022
142022
Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems
C DŁnner, T Parnell, M Jaggi
NIPS 2017 - Advances in Neural Information Processing Systems, 4261-4270, 2017
142017
Performative power
M Hardt, M Jagadeesan, C Mendler-DŁnner
NeurIPS 2022 - Advances in Neural Information Processing Systems, 2022
82022
Load-balancing training of recommender system for heterogeneous systems
K Atasu, C Duenner, T Mittelholzer, T Parnell, C Pozidis, M Vlachos
US Patent 10,839,255, 2020
82020
Tera-scale coordinate descent on GPUs
T Parnell, C DŁnner, K Atasu, M Sifalakis, H Pozidis
FGCS - Future Generation Computer Systems 108, 1173-1191, 2020
82020
Differentially Private Stochastic Coordinate Descent
G Damaskinos, C Mendler-DŁnner, R Guerraoui, N Papandreou, ...
AAAI 2021 - Advancement of Artificial Intelligence, 2020
82020
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