Alex Gittens

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 42

Top Topics

Visual Representations

Ridge Regression

Top Venues

J. Mach. Learn. Res.

Publications

Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin
Aligners: Decoupling LLMs and Alignment. Tiny Papers @ ICLR (2024)
Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin
Aligners: Decoupling LLMs and Alignment. CoRR (2024)
Anik Saha, Oktie Hassanzadeh, Alex Gittens, Jian Ni, Kavitha Srinivas, Bülent Yener
A Cross-Domain Evaluation of Approaches for Causal Knowledge Extraction. CoRR (2023)
Huzaifa Arif, Alex Gittens, Pin-Yu Chen
Reprogrammable-FL: Improving Utility-Privacy Tradeoff in Federated Learning via Model Reprogramming. SaTML (2023)
Deniz Koyuncu, Alex Gittens, Bülent Yener, Moti Yung
Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning. KDD (2023)
Anik Saha, Oktie Hassanzadeh, Alex Gittens, Jian Ni, Kavitha Srinivas, Bülent Yener
Improving Neural Ranking Models with Traditional IR Methods. CoRR (2023)
Alex Gittens, Malik Magdon-Ismail
Regression. CoRR (2023)
Deniz Koyuncu, Alex Gittens, Bülent Yener, Moti Yung
Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning. CoRR (2023)
Lilian Ngweta, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin
Simple Disentanglement of Style and Content in Visual Representations. ICML (2023)
Lilian Ngweta, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin
Simple Disentanglement of Style and Content in Visual Representations. CoRR (2023)
Anik Saha, Alex Gittens, Bülent Yener
Word Sense Induction with Knowledge Distillation from BERT. CoRR (2023)
Anik Saha, Alex Gittens, Jian Ni, Oktie Hassanzadeh, Bülent Yener, Kavitha Srinivas
SPOCK @ Causal News Corpus 2022: Cause-Effect-Signal Span Detection Using Span-Based and Sequence Tagging Models. CASE@EMNLP (2022)
Alex Gittens, Bülent Yener, Moti Yung
An Adversarial Perspective on Accuracy, Robustness, Fairness, and Privacy: Multilateral-Tradeoffs in Trustworthy ML. IEEE Access 10 (2022)
Nidhi Rastogi, Sharmishtha Dutta, Alex Gittens, Mohammed J. Zaki, Charu C. Aggarwal
TINKER: A framework for Open source Cyberthreat Intelligence. TrustCom (2022)
Dong Hu, Shashanka Ubaru, Alex Gittens, Kenneth L. Clarkson, Lior Horesh, Vassilis Kalantzis
Sparse Graph Based Sketching for Fast Numerical Linear Algebra. ICASSP (2021)
Kevin Kim, Alex Gittens
Learning Fair Canonical Polyadical Decompositions using a Kernel Independence Criterion. CoRR (2021)
Gabriel Orlanski, Alex Gittens
Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generation. CoRR (2021)
Nidhi Rastogi, Sharmishtha Dutta, Christian Ryan, Mohammad Zaki, Alex Gittens, Charu C. Aggarwal
Information Prediction using Knowledge Graphs for Contextual Malware Threat Intelligence. CoRR (2021)
Daniel Park, Haidar Khan, Azer Khan, Alex Gittens, Bülent Yener
Output Randomization: A Novel Defense for both White-box and Black-box Adversarial Models. CoRR (2021)
Dong Hu, Alex Gittens, Malik Magdon-Ismail
NoisyCUR: An algorithm for two-cost budgeted matrix completion. CoRR (2021)
Dong Hu, Shashanka Ubaru, Alex Gittens, Kenneth L. Clarkson, Lior Horesh, Vassilis Kalantzis
Sparse graph based sketching for fast numerical linear algebra. CoRR (2021)
Nidhi Rastogi, Sharmishtha Dutta, Mohammed J. Zaki, Alex Gittens, Charu C. Aggarwal
MALOnt: An Ontology for Malware Threat Intelligence. CoRR (2020)
Dong Hu, Alex Gittens, Malik Magdon-Ismail
NoisyCUR: An Algorithm for Two-Cost Budgeted Matrix Completion. ECML/PKDD (1) (2020)
Alex Gittens, Kareem S. Aggour, Bülent Yener
Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition. ICML (2020)
Alex Gittens, Kai Rothauge, Shusen Wang, Michael W. Mahoney, Jey Kottalam, Lisa Gerhardt, Prabhat, Michael F. Ringenburg, Kristyn J. Maschhoff
Alchemist: An Apache Spark ⇔ MPI interface. Concurr. Comput. Pract. Exp. 31 (16) (2019)
Malik Magdon-Ismail, Alex Gittens
Fast Fixed Dimension L2-Subspace Embeddings of Arbitrary Accuracy, With Application to L1 and L2 Tasks. CoRR (2019)
Bo Liu, Liping Jing, Jia Li, Jian Yu, Alex Gittens, Michael W. Mahoney
Group Collaborative Representation for Image Set Classification. Int. J. Comput. Vis. 127 (2) (2019)
Shusen Wang, Alex Gittens, Michael W. Mahoney
Scalable Kernel K-Means Clustering with Nystr\"om Approximation: Relative-Error Bounds. J. Mach. Learn. Res. 20 (2019)
Alex Gittens, Kai Rothauge, Shusen Wang, Michael W. Mahoney, Lisa Gerhardt, Prabhat, Jey Kottalam, Michael F. Ringenburg, Kristyn J. Maschhoff
Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist. KDD (2018)
Alex Gittens, Kai Rothauge, Shusen Wang, Michael W. Mahoney, Lisa Gerhardt, Prabhat, Jey Kottalam, Michael F. Ringenburg, Kristyn J. Maschhoff
Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist. CoRR (2018)
Kareem S. Aggour, Alex Gittens, Bülent Yener
Accelerating a Distributed CPD Algorithm for Large Dense, Skewed Tensors. IEEE BigData (2018)
Alex Gittens, Kai Rothauge, Shusen Wang, Michael W. Mahoney, Jey Kottalam, Lisa Gerhardt, Prabhat, Michael F. Ringenburg, Kristyn J. Maschhoff
Alchemist: An Apache Spark MPI Interface. CoRR (2018)
Shusen Wang, Alex Gittens, Michael W. Mahoney
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging. CoRR (2017)
Shusen Wang, Alex Gittens, Michael W. Mahoney
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging. J. Mach. Learn. Res. 18 (2017)
Alex Gittens, Dimitris Achlioptas, Michael W. Mahoney
Skip-Gram - Zipf + Uniform = Vector Additivity. ACL (1) (2017)
Stephen Tu, Shivaram Venkataraman, Ashia C. Wilson, Alex Gittens, Michael I. Jordan, Benjamin Recht
Breaking Locality Accelerates Block Gauss-Seidel. ICML (2017)
Shusen Wang, Alex Gittens, Michael W. Mahoney
Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds. CoRR (2017)
Shusen Wang, Alex Gittens, Michael W. Mahoney
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging. ICML (2017)
Alex Gittens, Jey Kottalam, Jiyan Yang, Michael F. Ringenburg, Jatin Chhugani, Evan Racah, Mohitdeep Singh, Yushu Yao, Curt Fischer, Oliver Rübel, Benjamin P. Bowen, Norman G. Lewis, Michael W. Mahoney, Venkat Krishnamurthy, Prabhat
A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark. IPDPS Workshops (2016)
Alex Gittens, Aditya Devarakonda, Evan Racah, Michael F. Ringenburg, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat
Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies. IEEE BigData (2016)
Alex Gittens, Aditya Devarakonda, Evan Racah, Michael F. Ringenburg, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat
Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies. CoRR (2016)
Alex Gittens, Michael W. Mahoney
Revisiting the Nystrom Method for Improved Large-scale Machine Learning. J. Mach. Learn. Res. 17 (2016)
Jiyan Yang, Alex Gittens
Tensor machines for learning target-specific polynomial features. CoRR (2015)
Christos Boutsidis, Prabhanjan Kambadur, Alex Gittens
Spectral Clustering via the Power Method - Provably. ICML (2015)
Da Kuang, Alex Gittens, Raffay Hamid
Hardware compliant approximate image codes. CVPR (2015)
Raffay Hamid, Ying Xiao, Alex Gittens, Dennis DeCoste
Compact Random Feature Maps. ICML (2014)
Alex Gittens, Michael W. Mahoney
Revisiting the Nystrom Method for Improved Large-Scale Machine Learning CoRR (2013)
Alex Gittens, Michael W. Mahoney
Revisiting the Nystrom method for improved large-scale machine learning. ICML (3) (2013)
Alex Gittens, Prabhanjan Kambadur, Christos Boutsidis
Approximate Spectral Clustering via Randomized Sketching. CoRR (2013)
Raffay Hamid, Ying Xiao, Alex Gittens, Dennis DeCoste
Compact Random Feature Maps. CoRR (2013)
Christos Boutsidis, Alex Gittens
Improved Matrix Algorithms via the Subsampled Randomized Hadamard Transform. SIAM J. Matrix Anal. Appl. 34 (3) (2013)
Christos Boutsidis, Alex Gittens
Improved matrix algorithms via the Subsampled Randomized Hadamard Transform CoRR (2012)
Alex Gittens
The spectral norm error of the naive Nystrom extension CoRR (2011)