Alex Gittens
Orcid: 0000-0003-3482-0157
According to our database1,
Alex Gittens
authored at least 42 papers
between 2011 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on cs.rpi.edu
On csauthors.net:
Bibliography
2024
CoRR, 2024
Exploiting the Data Gap: Utilizing Non-ignorable Missingness to Manipulate Model Learning.
CoRR, 2024
CoRR, 2024
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
2023
Reprogrammable-FL: Improving Utility-Privacy Tradeoff in Federated Learning via Model Reprogramming.
Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023
Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Proceedings of the International Conference on Machine Learning, 2023
2022
An Adversarial Perspective on Accuracy, Robustness, Fairness, and Privacy: Multilateral-Tradeoffs in Trustworthy ML.
IEEE Access, 2022
Proceedings of the IEEE International Conference on Trust, 2022
SPOCK @ Causal News Corpus 2022: Cause-Effect-Signal Span Detection Using Span-Based and Sequence Tagging Models.
Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text, 2022
2021
Output Randomization: A Novel Defense for both White-box and Black-box Adversarial Models.
CoRR, 2021
Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generation.
CoRR, 2021
Learning Fair Canonical Polyadical Decompositions using a Kernel Independence Criterion.
CoRR, 2021
Proceedings of the IEEE International Conference on Acoustics, 2021
2020
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Scalable Kernel K-Means Clustering with Nystr\"om Approximation: Relative-Error Bounds.
J. Mach. Learn. Res., 2019
Int. J. Comput. Vis., 2019
Fast Fixed Dimension L2-Subspace Embeddings of Arbitrary Accuracy, With Application to L1 and L2 Tasks.
CoRR, 2019
2018
Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018
2017
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging.
J. Mach. Learn. Res., 2017
Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds.
CoRR, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017
2016
J. Mach. Learn. Res., 2016
Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies.
CoRR, 2016
A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016
Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016
2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015
2014
Proceedings of the 31th International Conference on Machine Learning, 2014
2013
SIAM J. Matrix Anal. Appl., 2013
2011