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2020 – today
- 2024
[j8]Deniz Koyuncu
, Alex Gittens, Bülent Yener, Moti Yung:
Adversarial Missingness Attacks on Causal Structure Learning. ACM Trans. Intell. Syst. Technol. 15(6): 119:1-119:60 (2024)- [c21]Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin:
Aligners: Decoupling LLMs and Alignment. EMNLP (Findings) 2024: 13785-13802 - [c20]Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin:
Aligners: Decoupling LLMs and Alignment. Tiny Papers @ ICLR 2024 - [i29]Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin:
Aligners: Decoupling LLMs and Alignment. CoRR abs/2403.04224 (2024) - [i28]Arvind Rathnashyam, Alex Gittens:
Iterative thresholding for non-linear learning in the strong ε-contamination model. CoRR abs/2409.03703 (2024) - [i27]Deniz Koyuncu, Alex Gittens, Bülent Yener, Moti Yung:
Exploiting the Data Gap: Utilizing Non-ignorable Missingness to Manipulate Model Learning. CoRR abs/2409.04407 (2024) - [i26]Sharmishtha Dutta, Alex Gittens, Mohammed J. Zaki, Charu C. Aggarwal:
Replacing Paths with Connection-Biased Attention for Knowledge Graph Completion. CoRR abs/2410.00876 (2024) - 2023
- [c19]Lilian Ngweta, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin:
Simple Disentanglement of Style and Content in Visual Representations. ICML 2023: 26063-26086 - [c18]Deniz Koyuncu, Alex Gittens, Bülent Yener, Moti Yung:
Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning. KDD 2023: 1164-1175 - [c17]Huzaifa Arif, Alex Gittens, Pin-Yu Chen:
Reprogrammable-FL: Improving Utility-Privacy Tradeoff in Federated Learning via Model Reprogramming. SaTML 2023: 197-209 - [i25]Lilian Ngweta, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin:
Simple Disentanglement of Style and Content in Visual Representations. CoRR abs/2302.09795 (2023) - [i24]Anik Saha, Alex Gittens, Bülent Yener:
Word Sense Induction with Knowledge Distillation from BERT. CoRR abs/2304.10642 (2023) - [i23]Alex Gittens, Malik Magdon-Ismail:
Reduced Label Complexity For Tight 𝓁2 Regression. CoRR abs/2305.07486 (2023) - [i22]Deniz Koyuncu, Alex Gittens, Bülent Yener, Moti Yung:
Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning. CoRR abs/2305.20043 (2023) - [i21]Anik Saha, Oktie Hassanzadeh, Alex Gittens, Jian Ni, Kavitha Srinivas, Bülent Yener:
A Cross-Domain Evaluation of Approaches for Causal Knowledge Extraction. CoRR abs/2308.03891 (2023) - [i20]Anik Saha, Oktie Hassanzadeh, Alex Gittens, Jian Ni, Kavitha Srinivas, Bülent Yener:
Improving Neural Ranking Models with Traditional IR Methods. CoRR abs/2308.15027 (2023) - 2022
- [j7]Alex Gittens, Bülent Yener, Moti Yung:
An Adversarial Perspective on Accuracy, Robustness, Fairness, and Privacy: Multilateral-Tradeoffs in Trustworthy ML. IEEE Access 10: 120850-120865 (2022) - [c16]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: 133-137 - [c15]Nidhi Rastogi, Sharmishtha Dutta, Alex Gittens, Mohammed J. Zaki, Charu C. Aggarwal:
TINKER: A framework for Open source Cyberthreat Intelligence. TrustCom 2022: 1569-1574 - 2021
- [c14]Dong Hu, Shashanka Ubaru, Alex Gittens, Kenneth L. Clarkson, Lior Horesh, Vassilis Kalantzis:
Sparse Graph Based Sketching for Fast Numerical Linear Algebra. ICASSP 2021: 3255-3259 - [i19]Nidhi Rastogi, Sharmishtha Dutta, Mohammed J. Zaki, Alex Gittens, Charu C. Aggarwal:
TINKER: A framework for Open source Cyberthreat Intelligence. CoRR abs/2102.05571 (2021) - [i18]Dong Hu, Shashanka Ubaru, Alex Gittens, Kenneth L. Clarkson, Lior Horesh, Vassilis Kalantzis:
Sparse graph based sketching for fast numerical linear algebra. CoRR abs/2102.05758 (2021) - [i17]Dong Hu, Alex Gittens, Malik Magdon-Ismail:
NoisyCUR: An algorithm for two-cost budgeted matrix completion. CoRR abs/2104.08026 (2021) - [i16]Kevin Kim, Alex Gittens:
Learning Fair Canonical Polyadical Decompositions using a Kernel Independence Criterion. CoRR abs/2104.13504 (2021) - [i15]Gabriel Orlanski, Alex Gittens:
Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generation. CoRR abs/2106.04447 (2021) - [i14]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 abs/2107.03806 (2021) - 2020
- [c13]Alex Gittens, Kareem S. Aggour, Bülent Yener:
Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition. ICML 2020: 3566-3575 - [c12]Dong Hu, Alex Gittens, Malik Magdon-Ismail:
NoisyCUR: An Algorithm for Two-Cost Budgeted Matrix Completion. ECML/PKDD (1) 2020: 746-761 - [i13]Nidhi Rastogi, Sharmishtha Dutta, Mohammed J. Zaki, Alex Gittens, Charu C. Aggarwal:
MALOnt: An Ontology for Malware Threat Intelligence. CoRR abs/2006.11446 (2020)
2010 – 2019
- 2019
- [j6]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) - [j5]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): 181-206 (2019) - [j4]Shusen Wang, Alex Gittens, Michael W. Mahoney:
Scalable Kernel K-Means Clustering with Nystr\"om Approximation: Relative-Error Bounds. J. Mach. Learn. Res. 20: 12:1-12:49 (2019) - [i12]Malik Magdon-Ismail, Alex Gittens:
Fast Fixed Dimension L2-Subspace Embeddings of Arbitrary Accuracy, With Application to L1 and L2 Tasks. CoRR abs/1909.12580 (2019) - 2018
- [c11]Kareem S. Aggour, Alex Gittens, Bülent Yener:
Accelerating a Distributed CPD Algorithm for Large Dense, Skewed Tensors. IEEE BigData 2018: 408-417 - [c10]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: 293-301 - [i11]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 abs/1805.11800 (2018) - [i10]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 abs/1806.01270 (2018) - 2017
- [j3]Shusen Wang, Alex Gittens, Michael W. Mahoney:
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging. J. Mach. Learn. Res. 18: 218:1-218:50 (2017) - [c9]Alex Gittens, Dimitris Achlioptas, Michael W. Mahoney:
Skip-Gram - Zipf + Uniform = Vector Additivity. ACL (1) 2017: 69-76 - [c8]Stephen Tu, Shivaram Venkataraman, Ashia C. Wilson, Alex Gittens, Michael I. Jordan, Benjamin Recht:
Breaking Locality Accelerates Block Gauss-Seidel. ICML 2017: 3482-3491 - [c7]Shusen Wang, Alex Gittens, Michael W. Mahoney:
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging. ICML 2017: 3608-3616 - [i9]Shusen Wang, Alex Gittens, Michael W. Mahoney:
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging. CoRR abs/1702.04837 (2017) - [i8]Shusen Wang, Alex Gittens, Michael W. Mahoney:
Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds. CoRR abs/1706.02803 (2017) - 2016
- [j2]Alex Gittens, Michael W. Mahoney:
Revisiting the Nystrom Method for Improved Large-scale Machine Learning. J. Mach. Learn. Res. 17: 117:1-117:65 (2016) - [c6]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: 204-213 - [c5]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: 1403-1412 - [i7]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 abs/1607.01335 (2016) - 2015
- [c4]Da Kuang, Alex Gittens, Raffay Hamid:
Hardware compliant approximate image codes. CVPR 2015: 924-932 - [c3]Christos Boutsidis, Prabhanjan Kambadur, Alex Gittens:
Spectral Clustering via the Power Method - Provably. ICML 2015: 40-48 - [i6]Jiyan Yang, Alex Gittens:
Tensor machines for learning target-specific polynomial features. CoRR abs/1504.01697 (2015) - 2014
- [c2]Raffay Hamid, Ying Xiao, Alex Gittens, Dennis DeCoste:
Compact Random Feature Maps. ICML 2014: 19-27 - 2013
- [j1]Christos Boutsidis, Alex Gittens:
Improved Matrix Algorithms via the Subsampled Randomized Hadamard Transform. SIAM J. Matrix Anal. Appl. 34(3): 1301-1340 (2013) - [c1]Alex Gittens, Michael W. Mahoney:
Revisiting the Nystrom method for improved large-scale machine learning. ICML (3) 2013: 567-575 - [i5]Alex Gittens, Michael W. Mahoney:
Revisiting the Nystrom Method for Improved Large-Scale Machine Learning. CoRR abs/1303.1849 (2013) - [i4]Alex Gittens, Prabhanjan Kambadur, Christos Boutsidis:
Approximate Spectral Clustering via Randomized Sketching. CoRR abs/1311.2854 (2013) - [i3]Raffay Hamid, Ying Xiao, Alex Gittens, Dennis DeCoste:
Compact Random Feature Maps. CoRR abs/1312.4626 (2013) - 2012
- [i2]Christos Boutsidis, Alex Gittens:
Improved matrix algorithms via the Subsampled Randomized Hadamard Transform. CoRR abs/1204.0062 (2012) - 2011
- [i1]Alex Gittens:
The spectral norm error of the naive Nystrom extension. CoRR abs/1110.5305 (2011)
Coauthor Index
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