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Publication search results
found 112 matches
- 2024
- Majid Daliri, Juliana Freire, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang:
Sampling Methods for Inner Product Sketching. Proc. VLDB Endow. 17(9): 2185-2197 (2024) - Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco:
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. AAAI 2024: 21554-21562 - Aarshvi Gajjar, Wai Ming Tai, Xingyu Xu, Chinmay Hegde, Christopher Musco, Yi Li:
Agnostic Active Learning of Single Index Models with Linear Sample Complexity. COLT 2024: 1715-1754 - Yujia Jin, Ishani Karmarkar, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh:
Faster Spectral Density Estimation and Sparsification in the Nuclear Norm (Extended Abstract). COLT 2024: 2722 - Atsushi Shimizu, Xiaoou Cheng, Christopher Musco, Jonathan Weare:
Improved Active Learning via Dependent Leverage Score Sampling. ICLR 2024 - Raphael A. Meyer, Cameron Musco, Christopher Musco:
On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. SODA 2024: 811-845 - Majid Daliri, Juliana Freire, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang:
Simple Analysis of Priority Sampling. SOSA 2024: 224-229 - Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco:
Fixed-sparsity matrix approximation from matrix-vector products. CoRR abs/2402.09379 (2024) - Michal Derezinski, Christopher Musco, Jiaming Yang:
Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning. CoRR abs/2405.05865 (2024) - Aarshvi Gajjar, Wai Ming Tai, Xingyu Xu, Chinmay Hegde, Christopher Musco, Yi Li:
Agnostic Active Learning of Single Index Models with Linear Sample Complexity. CoRR abs/2405.09312 (2024) - Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel:
Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits. CoRR abs/2405.18680 (2024) - Yujia Jin, Ishani Karmarkar, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh:
Faster Spectral Density Estimation and Sparsification in the Nuclear Norm. CoRR abs/2406.07521 (2024) - Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson:
Near-optimal hierarchical matrix approximation from matrix-vector products. CoRR abs/2407.04686 (2024) - Majid Daliri, Christopher Musco, Ananda Theertha Suresh:
Coupling without Communication and Drafter-Invariant Speculative Decoding. CoRR abs/2408.07978 (2024) - Cameron Musco, Christopher Musco, Lucas Rosenblatt, Apoorv Vikram Singh:
Sharper Bounds for Chebyshev Moment Matching with Applications to Differential Privacy and Beyond. CoRR abs/2408.12385 (2024) - R. Teal Witter, Christopher Musco:
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm. CoRR abs/2409.04500 (2024) - Christopher Musco, R. Teal Witter:
Provably Accurate Shapley Value Estimation via Leverage Score Sampling. CoRR abs/2410.01917 (2024) - 2023
- Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco:
Low-Memory Krylov Subspace Methods for Optimal Rational Matrix Function Approximation. SIAM J. Matrix Anal. Appl. 44(2): 670-692 (2023) - Aarshvi Gajjar, Christopher Musco, Chinmay Hegde:
Active Learning for Single Neuron Models with Lipschitz Non-Linearities. AISTATS 2023: 4101-4113 - Yujia Jin, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh:
Moments, Random Walks, and Limits for Spectrum Approximation. COLT 2023: 5373-5394 - Chuhan Yang, Christopher Musco:
Efficient Block Approximate Matrix Multiplication. ESA 2023: 103:1-103:15 - Xinyu Luo, Christopher Musco, Cas Widdershoven:
Dimensionality Reduction for General KDE Mode Finding. ICML 2023: 23067-23082 - Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian:
Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS 2023 - Aline Bessa, Majid Daliri, Juliana Freire, Cameron Musco, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang:
Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation. PODS 2023: 169-181 - Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Near-Linear Sample Complexity for Lp Polynomial Regression. SODA 2023: 3959-4025 - Prathamesh Dharangutte, Christopher Musco:
A Tight Analysis of Hutchinson's Diagonal Estimator. SOSA 2023: 353-364 - Aline Bessa, Majid Daliri, Juliana Freire, Cameron Musco, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang:
Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation. CoRR abs/2301.05811 (2023) - Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco:
Near-Optimality Guarantees for Approximating Rational Matrix Functions by the Lanczos Method. CoRR abs/2303.03358 (2023) - Raphael A. Meyer, Cameron Musco, Christopher Musco:
On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. CoRR abs/2305.02535 (2023) - Xinyu Luo, Christopher Musco, Cas Widdershoven:
Dimensionality Reduction for General KDE Mode Finding. CoRR abs/2305.18755 (2023)
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