Celestine Dünner

CoRR, 2024

Adjusting Pretrained Backbones for Performativity.

[BibT_eX]

[DOI]

Francesco Locatello

CoRR, 2024

Evaluating language models as risk scores.

[BibT_eX]

[DOI]

André F. Cruz

CoRR, 2024

An engine not a camera: Measuring performative power of online search.

[BibT_eX]

[DOI]

Gabriele Carovano

CoRR, 2024

Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists.

[BibT_eX]

[DOI]

Joachim Baumann

CoRR, 2024

Causal Inference out of Control: Estimating Performativity without Treatment Randomization.

[BibT_eX]

[DOI]

Gary Cheng

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Performative Prediction: Past and Future.

[BibT_eX]

[DOI]

CoRR, 2023

Questioning the Survey Responses of Large Language Models.

[BibT_eX]

[DOI]

Ricardo Dominguez-Olmedo

CoRR, 2023

Causal Inference out of Control: Estimating the Steerability of Consumption.

[BibT_eX]

[DOI]

Gary Cheng

CoRR, 2023

Collaborative Learning via Prediction Consensus.

[BibT_eX]

[DOI]

Dongyang Fan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Algorithmic Collective Action in Machine Learning.

[BibT_eX]

[DOI]

Eric Mazumdar

Proceedings of the International Conference on Machine Learning, 2023

2022

Predicting from Predictions.

[BibT_eX]

[DOI]

Frances Ding

Yixin Wang

CoRR, 2022

Anticipating Performativity by Predicting from Predictions.

[BibT_eX]

[DOI]

Frances Ding

Yixin Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Performative Power.

[BibT_eX]

[DOI]

Meena Jagadeesan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Regret Minimization with Performative Feedback.

[BibT_eX]

[DOI]

Meena Jagadeesan

Proceedings of the International Conference on Machine Learning, 2022

2021

Test-time Collective Prediction.

[BibT_eX]

[DOI]

Wenshuo Guo

Stephen Bates

Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Alternative Microfoundations for Strategic Classification.

[BibT_eX]

[DOI]

Meena Jagadeesan

Proceedings of the 38th International Conference on Machine Learning, 2021

Differentially Private Stochastic Coordinate Descent.

[BibT_eX]

[DOI]

Georgios Damaskinos

Rachid Guerraoui

Nikolaos Papandreou

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Tera-scale coordinate descent on GPUs.

[BibT_eX]

[DOI]

Future Gener. Comput. Syst., 2020

Revisiting Design Choices in Proximal Policy Optimization.

[BibT_eX]

[DOI]

Chloe Ching-Yun Hsu

CoRR, 2020

Stochastic Optimization for Performative Prediction.

[BibT_eX]

[DOI]

Juan C. Perdomo

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Performative Prediction.

[BibT_eX]

[DOI]

Juan C. Perdomo

Proceedings of the 37th International Conference on Machine Learning, 2020

Randomized Block-Diagonal Preconditioning for Parallel Learning.

[BibT_eX]

[DOI]

Aurélien Lucchi

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

System-Aware Algorithms For Machine Learning.

[BibT_eX]

[DOI]

PhD thesis, 2019

Addressing Interpretability and Cold-Start in Matrix Factorization for Recommender Systems.

[BibT_eX]

[DOI]

Michail Vlachos

Reinhard Heckel

Vassilios G. Vassiliadis

Kubilay Atasu

IEEE Trans. Knowl. Data Eng., 2019

Breadth-first, Depth-next Training of Random Forests.

[BibT_eX]

[DOI]

Haris Pozidis

CoRR, 2019

Addressing Algorithmic Bottlenecks in Elastic Machine Learning with Chicle.

[BibT_eX]

[DOI]

Michael Kaufmann

Kornilios Kourtis

Adrian Schüpbach

CoRR, 2019

Sampling Acquisition Functions for Batch Bayesian Optimization.

[BibT_eX]

[DOI]

Alessandro De Palma

Andreea Anghel

Haralampos Pozidis

CoRR, 2019

SySCD: A System-Aware Parallel Coordinate Descent Algorithm.

[BibT_eX]

[DOI]

Nikolas Ioannou

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On Linear Learning with Manycore Processors.

[BibT_eX]

[DOI]

Eliza Wszola

Markus Püschel

Proceedings of the 26th IEEE International Conference on High Performance Computing, 2019

2018

Parallel training of linear models without compromising convergence.

[BibT_eX]

[DOI]

CoRR, 2018

Snap ML: A Hierarchical Framework for Machine Learning.

[BibT_eX]

[DOI]

Dimitrios Sarigiannis

Nikolas Ioannou

Andreea Anghel

Haralampos Pozidis

CoRR, 2018

Snap ML: A Hierarchical Framework for Machine Learning.

[BibT_eX]

[DOI]

Dimitrios Sarigiannis

Nikolas Ioannou

Andreea Anghel

Gummadi Ravi

Madhusudanan Kandasamy

Haralampos Pozidis

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Distributed Second-Order Algorithm You Can Trust.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Efficient Use of Limited-Memory Resources to Accelerate Linear Learning.

[BibT_eX]

[DOI]

CoRR, 2017

Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Large-Scale Stochastic Learning Using GPUs.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium Workshops, 2017

High-Performance Recommender System Training Using Co-Clustering on CPU/GPU Clusters.

[BibT_eX]

[DOI]

Proceedings of the 46th International Conference on Parallel Processing, 2017

Scalable and Interpretable Product Recommendations via Overlapping Co-Clustering.

[BibT_eX]

[DOI]

Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017

Understanding and optimizing the performance of distributed machine learning applications on apache spark.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

Linear-complexity relaxed word Mover's distance with GPU acceleration.

[BibT_eX]

[DOI]

Vasileios Vasileiadis

Michail Vlachos

Cesar Berrospi

Abdel Labbi

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

Capacity of the MLC NAND Flash Channel.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2016

High-Performance Distributed Machine Learning using Apache SPARK.

[BibT_eX]

[DOI]

CoRR, 2016

Primal-Dual Rates and Certificates.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Endurance limits of MLC NAND flash.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Communications, 2015

2014

Power control for cellular networks with large antenna arrays and ubiquitous relaying.

[BibT_eX]

[DOI]

Raphael T. L. Rolny