Power control for cellular networks with large antenna arrays and ubiquitous relaying. - Raphael T. L. Rolny; Celestine Dünner; Armin Wittneben (SPAWC, 2014)

Endurance limits of MLC NAND flash. - Thomas P. Parnell; Celestine Dünner; Thomas Mittelholzer; Nikolaos Papandreou; Haralampos Pozidis (ICC, 2015)

Primal-Dual Rates and Certificates. - Celestine Dünner; Simone Forte; Martin Takác 001; Martin Jaggi (ICML, 2016)

High-Performance Distributed Machine Learning using Apache SPARK. - Celestine Dünner; Thomas P. Parnell; Kubilay Atasu; Manolis Sifalakis; Haralampos Pozidis (CoRR, 2016)

Capacity of the MLC NAND Flash Channel. - Thomas P. Parnell; Celestine Dünner; Thomas Mittelholzer; Nikolaos Papandreou (IEEE J. Sel. Areas Commun., 2016)

Linear-complexity relaxed word Mover's distance with GPU acceleration. - Kubilay Atasu; Thomas P. Parnell; Celestine Dünner; Manolis Sifalakis; Haralampos Pozidis; Vasileios Vasileiadis; Michail Vlachos; Cesar Berrospi; Abdel Labbi (IEEE BigData, 2017)

Understanding and optimizing the performance of distributed machine learning applications on apache spark. - Celestine Dünner; Thomas P. Parnell; Kubilay Atasu; Manolis Sifalakis; Haralampos Pozidis (IEEE BigData, 2017)

Scalable and Interpretable Product Recommendations via Overlapping Co-Clustering. - Reinhard Heckel; Michail Vlachos; Thomas P. Parnell; Celestine Dünner (ICDE, 2017)

High-Performance Recommender System Training Using Co-Clustering on CPU/GPU Clusters. - Kubilay Atasu; Thomas P. Parnell; Celestine Dünner; Michail Vlachos; Haralampos Pozidis (ICPP, 2017)

Large-Scale Stochastic Learning Using GPUs. - Thomas P. Parnell; Celestine Dünner; Kubilay Atasu; Manolis Sifalakis; Haris Pozidis (IPDPS Workshops, 2017)

Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems. - Celestine Dünner; Thomas P. Parnell; Martin Jaggi (NIPS, 2017)

Efficient Use of Limited-Memory Resources to Accelerate Linear Learning. - Celestine Dünner; Thomas P. Parnell; Martin Jaggi (CoRR, 2017)

A Distributed Second-Order Algorithm You Can Trust. - Celestine Dünner; Aurélien Lucchi; Matilde Gargiani; An Bian; Thomas Hofmann 001; Martin Jaggi (ICML, 2018)

Snap ML: A Hierarchical Framework for Machine Learning. - Celestine Dünner; Thomas P. Parnell; Dimitrios Sarigiannis; Nikolas Ioannou; Andreea Anghel; Gummadi Ravi; Madhusudanan Kandasamy; Haralampos Pozidis (NeurIPS, 2018)

Snap ML: A Hierarchical Framework for Machine Learning. - Celestine Dünner; Thomas P. Parnell; Dimitrios Sarigiannis; Nikolas Ioannou; Andreea Anghel; Haralampos Pozidis (CoRR, 2018)

Parallel training of linear models without compromising convergence. - Nikolas Ioannou; Celestine Dünner; Kornilios Kourtis; Thomas P. Parnell (CoRR, 2018)

On Linear Learning with Manycore Processors. - Eliza Wszola; Celestine Mendler-Dünner; Martin Jaggi; Markus Püschel (HiPC, 2019)

SySCD: A System-Aware Parallel Coordinate Descent Algorithm. - Nikolas Ioannou; Celestine Mendler-Dünner; Thomas P. Parnell (NeurIPS, 2019)

Sampling Acquisition Functions for Batch Bayesian Optimization. - Alessandro De Palma; Celestine Mendler-Dünner; Thomas P. Parnell; Andreea Anghel; Haralampos Pozidis (CoRR, 2019)

Addressing Algorithmic Bottlenecks in Elastic Machine Learning with Chicle. - Michael Kaufmann 005; Kornilios Kourtis; Celestine Mendler-Dünner; Adrian Schüpbach; Thomas P. Parnell (CoRR, 2019)

Breadth-first, Depth-next Training of Random Forests. - Andreea Anghel; Nikolas Ioannou; Thomas P. Parnell; Nikolaos Papandreou; Celestine Mendler-Dünner; Haris Pozidis (CoRR, 2019)

Addressing Interpretability and Cold-Start in Matrix Factorization for Recommender Systems. - Michail Vlachos; Celestine Dünner; Reinhard Heckel; Vassilios G. Vassiliadis; Thomas P. Parnell; Kubilay Atasu (IEEE Trans. Knowl. Data Eng., 2019)

System-Aware Algorithms For Machine Learning. - Celestine Mendler-Dünner (2019)

Randomized Block-Diagonal Preconditioning for Parallel Learning. - Celestine Mendler-Dünner; Aurélien Lucchi (ICML, 2020)

Performative Prediction. - Juan C. Perdomo; Tijana Zrnic; Celestine Mendler-Dünner; Moritz Hardt (ICML, 2020)

Stochastic Optimization for Performative Prediction. - Celestine Mendler-Dünner; Juan C. Perdomo; Tijana Zrnic; Moritz Hardt (NeurIPS, 2020)

Revisiting Design Choices in Proximal Policy Optimization. - Chloe Ching-Yun Hsu; Celestine Mendler-Dünner; Moritz Hardt (CoRR, 2020)

Tera-scale coordinate descent on GPUs. - Thomas P. Parnell; Celestine Dünner; Kubilay Atasu; Manolis Sifalakis; Haralampos Pozidis (Future Gener. Comput. Syst., 2020)

Differentially Private Stochastic Coordinate Descent. - Georgios Damaskinos; Celestine Mendler-Dünner; Rachid Guerraoui; Nikolaos Papandreou; Thomas P. Parnell (AAAI, 2021)

Alternative Microfoundations for Strategic Classification. - Meena Jagadeesan; Celestine Mendler-Dünner; Moritz Hardt (ICML, 2021)

Test-time Collective Prediction. - Celestine Mendler-Dünner; Wenshuo Guo; Stephen Bates; Michael I. Jordan (NeurIPS, 2021)

Regret Minimization with Performative Feedback. - Meena Jagadeesan; Tijana Zrnic; Celestine Mendler-Dünner (ICML, 2022)

Performative Power. - Moritz Hardt; Meena Jagadeesan; Celestine Mendler-Dünner (NeurIPS, 2022)

Anticipating Performativity by Predicting from Predictions. - Celestine Mendler-Dünner; Frances Ding; Yixin Wang (NeurIPS, 2022)

Predicting from Predictions. - Celestine Mendler-Dünner; Frances Ding; Yixin Wang (CoRR, 2022)

Algorithmic Collective Action in Machine Learning. - Moritz Hardt; Eric Mazumdar; Celestine Mendler-Dünner; Tijana Zrnic (ICML, 2023)

Collaborative Learning via Prediction Consensus. - Dongyang Fan; Celestine Mendler-Dünner; Martin Jaggi (NeurIPS, 2023)

Causal Inference out of Control: Estimating the Steerability of Consumption. - Gary Cheng 004; Moritz Hardt; Celestine Mendler-Dünner (CoRR, 2023)

Performative Prediction: Past and Future. - Moritz Hardt; Celestine Mendler-Dünner (CoRR, 2023)

Causal Inference out of Control: Estimating Performativity without Treatment Randomization. - Gary Cheng 004; Moritz Hardt; Celestine Mendler-Dünner (ICML, 2024)

Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists. - Joachim Baumann 002; Celestine Mendler-Dünner (NeurIPS, 2024)

Evaluating language models as risk scores. - André F. Cruz; Moritz Hardt; Celestine Mendler-Dünner (NeurIPS, 2024)

Questioning the Survey Responses of Large Language Models. - Ricardo Dominguez-Olmedo; Moritz Hardt; Celestine Mendler-Dünner (NeurIPS, 2024)

An engine not a camera: Measuring performative power of online search. - Celestine Mendler-Dünner; Gabriele Carovano; Moritz Hardt (NeurIPS, 2024)

Adjusting Pretrained Backbones for Performativity. - Berker Demirel; Lingjing Kong; Kun Zhang 001; Theofanis Karaletsos; Celestine Mendler-Dünner; Francesco Locatello (CoRR, 2024)

Decline Now: A Combinatorial Model for Algorithmic Collective Action. - Dorothee Sigg; Moritz Hardt; Celestine Mendler-Dünner (CHI, 2025)

Performative Validity of Recourse Explanations. - Gunnar König; Hidde Fokkema; Timo Freiesleben; Celestine Mendler-Dünner; Ulrike von Luxburg (CoRR, 2025)