Alex Gittens

Malik Magdon-Ismail

CoRR, 2023

Word Sense Induction with Knowledge Distillation from BERT.

[BibT_eX]

[DOI]

Anik Saha

CoRR, 2023

Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning.

[BibT_eX]

[DOI]

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Simple Disentanglement of Style and Content in Visual Representations.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

An Adversarial Perspective on Accuracy, Robustness, Fairness, and Privacy: Multilateral-Tradeoffs in Trustworthy ML.

[BibT_eX]

[DOI]

Moti Yung

IEEE Access, 2022

TINKER: A framework for Open source Cyberthreat Intelligence.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

CoRR, 2021

Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generation.

[BibT_eX]

[DOI]

Gabriel Orlanski

CoRR, 2021

Learning Fair Canonical Polyadical Decompositions using a Kernel Independence Criterion.

[BibT_eX]

[DOI]

Kevin Kim

CoRR, 2021

Sparse Graph Based Sketching for Fast Numerical Linear Algebra.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

MALOnt: An Ontology for Malware Threat Intelligence.

[BibT_eX]

[DOI]

CoRR, 2020

NoisyCUR: An Algorithm for Two-Cost Budgeted Matrix Completion.

[BibT_eX]

[DOI]

Dong Hu

Malik Magdon-Ismail

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition.

[BibT_eX]

[DOI]

Kareem S. Aggour

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

2019

Scalable Kernel K-Means Clustering with Nystr\"om Approximation: Relative-Error Bounds.

[BibT_eX]

[DOI]

Shusen Wang

J. Mach. Learn. Res., 2019

Group Collaborative Representation for Image Set Classification.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2019

Fast Fixed Dimension L2-Subspace Embeddings of Arbitrary Accuracy, With Application to L1 and L2 Tasks.

[BibT_eX]

[DOI]

Malik Magdon-Ismail

CoRR, 2019

Alchemist: An Apache Spark ⇔ MPI interface.

[BibT_eX]

[DOI]

Kristyn J. Maschhoff

Concurr. Comput. Pract. Exp., 2019

2018

Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist.

[BibT_eX]

[DOI]

Kristyn J. Maschhoff

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Accelerating a Distributed CPD Algorithm for Large Dense, Skewed Tensors.

[BibT_eX]

[DOI]

Kareem S. Aggour

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging.

[BibT_eX]

[DOI]

Shusen Wang

J. Mach. Learn. Res., 2017

Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds.

[BibT_eX]

[DOI]

Shusen Wang

CoRR, 2017

Breaking Locality Accelerates Block Gauss-Seidel.

[BibT_eX]

[DOI]

Stephen Tu

Shivaram Venkataraman

Proceedings of the 34th International Conference on Machine Learning, 2017

Skip-Gram - Zipf + Uniform = Vector Additivity.

[BibT_eX]

[DOI]

Dimitris Achlioptas

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Revisiting the Nystrom Method for Improved Large-scale Machine Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2016

Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies.

[BibT_eX]

[DOI]

Aditya Devarakonda

Evan Racah

CoRR, 2016

A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark.

[BibT_eX]

[DOI]

Jey Kottalam

Jiyan Yang

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.

[BibT_eX]

[DOI]

Aditya Devarakonda

Evan Racah

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

Tensor machines for learning target-specific polynomial features.

[BibT_eX]

[DOI]

Jiyan Yang

CoRR, 2015

Spectral Clustering via the Power Method - Provably.

[BibT_eX]

[DOI]

Christos Boutsidis

Prabhanjan Kambadur

Proceedings of the 32nd International Conference on Machine Learning, 2015

Hardware compliant approximate image codes.

[BibT_eX]

[DOI]

Da Kuang

Raffay Hamid

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Compact Random Feature Maps.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Improved Matrix Algorithms via the Subsampled Randomized Hadamard Transform.

[BibT_eX]

[DOI]

Christos Boutsidis

SIAM J. Matrix Anal. Appl., 2013

Approximate Spectral Clustering via Randomized Sketching.

[BibT_eX]

[DOI]

Prabhanjan Kambadur

Christos Boutsidis

CoRR, 2013

2011

The spectral norm error of the naive Nystrom extension

[BibT_eX]

[DOI]