Cameron Musco

1. Principal Component Projection Without Principal Component Analysis
   2016/02/22 by Roy Frostig, Cameron Musco, Frostig, Roy +5 · 1 voice · 1 citation
   Computer Science · Mathematics · #Matrix Theory and Algorithms #Tensor decomposition and applications #Stochastic Gradient Optimization Techniques
2. Hutch++: Optimal Stochastic Trace Estimation
   2020/10/19 by Raphael A. Meyer, Cameron Musco, Meyer, Raphael A. +5 · 1 voice · 12 citations
   Computer Science · Mathematics · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #cs.DS #cs.LG #math.NA
3. Randomized Block Krylov Methods for Stronger and Faster Approximate\n Singular Value Decomposition
   2015/04/21 by Cameron Musco, Christopher Musco, Musco, Cameron +1 · 13 citations
   Computer Science · Engineering · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Matrix Theory and Algorithms #Numerical Analysis (math.NA) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
4. Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
   2018/04/26 by Haim Avron, Michael Kapralov, Avron, Haim +9 · 8 citations
   Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Gaussian Processes and Bayesian Inference #Stochastic Gradient Optimization Techniques
5. Single Pass Spectral Sparsification in Dynamic Streams
   2014/07/04 by Michael Kapralov, Yin Tat Lee, Kapralov, Michael +7 · 4 citations
   Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Complexity and Algorithms in Graphs
6. Efficient Intervention Design for Causal Discovery with Latents
   2020/05/24 by Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Addanki, Raghavendra +5 · 2 citations
   Computer Science · Decision Sciences · #AI-based Problem Solving and Planning #Bayesian Modeling and Causal Inference #Data Quality and Management #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. Faster Eigenvector Computation via Shift-and-Invert Preconditioning
   2016/05/26 by Dan Garber, Garber, Dan, Elad Hazan +11 · 3 citations
   Computer Science · Engineering · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Matrix Theory and Algorithms #Numerical Analysis (math.NA) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
8. Near Optimal Linear Algebra in the Online and Sliding Window Models
   2018/05/10 by Vladimir Braverman, Petros Drineas, Braverman, Vladimir +11 · 2 citations
   Engineering · Computer Science · Decision Sciences · #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Advanced Bandit Algorithms Research
9. Faster Kernel Matrix Algebra via Density Estimation
   2021/02/16 by Artūrs Bačkurs, Piotr Indyk, Backurs, Arturs +5 · 2 citations
   Computer Science · Engineering · Mathematics · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Tensor decomposition and applications
10. Near-Linear Sample Complexity for L_p Polynomial Regression
    2022/11/13 by Raphael A. Meyer, Meyer, Raphael A., Cameron Musco +7 · 2 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning and Algorithms #Machine Learning and Data Classification
11. InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity
    2020/05/29 by Sudhanshu Chanpuriya, Cameron Musco, Chanpuriya, Sudhanshu +1 · 1 citation
    Computer Science · #Advanced Graph Neural Networks #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Social and Information Networks (cs.SI) #Text and Document Classification Technologies #Topic Modeling
12. Sharper Bounds for Chebyshev Moment Matching, with Applications
    2024/08/22 by Cameron Musco, Christopher Musco, Musco, Cameron +5 · 2 citations
    Computer Science · Mathematics · #Bayesian Modeling and Causal Inference #Machine Learning and Algorithms #Statistical Methods and Inference
13. Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings
    2021/11/04 by Sudhanshu Chanpuriya, Ryan A. Rossi, Chanpuriya, Sudhanshu +11 · 1 citation
    Physics and Astronomy · Computer Science · Mathematics · #Complex Network Analysis Techniques #Advanced Graph Neural Networks #Graph theory and applications
14. Toeplitz Low-Rank Approximation with Sublinear Query Complexity
    2022/11/21 by Michael Kapralov, Hannah Lawrence, Kapralov, Michael +7 · 1 citation
    Engineering · Mathematics · Computer Science · #Sparse and Compressive Sensing Techniques #Tensor decomposition and applications #Stochastic Gradient Optimization Techniques
15. Recursive Sampling for the Nyström Method
    2016/05/24 by Cameron Musco, Christopher Musco, Musco, Cameron +1 · 1 citation
    Computer Science · Physics and Astronomy · #Stochastic Gradient Optimization Techniques #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference
16. Importance Sampling via Local Sensitivity
    2019/11/04 by Anant Raj, Raj, Anant, Cameron Musco +3 · 1 citation
    Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques