Search Results for author:
Found 8 papers, 2 papers with code
Stochastic gradient descent for streaming linear and rectified linear systems with Massart noise
We propose SGD-exp, a stochastic gradient descent approach for linear and ReLU regressions under Massart noise (adversarial semi-random corruption model) for the fully streaming setting.
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition
Sketch-and-project is a framework which unifies many known iterative methods for solving linear systems and their variants, as well as further extensions to non-linear optimization problems.
Nonlinear Matrix Approximation with Radial Basis Function Components
We introduce and investigate matrix approximation by decomposition into a sum of radial basis function (RBF) components.
Analysis of Legal Documents via Non-negative Matrix Factorization Methods
The California Innocence Project (CIP), a clinical law school program aiming to free wrongfully convicted prisoners, evaluates thousands of mails containing new requests for assistance and corresponding case files.
On a Guided Nonnegative Matrix Factorization
Fully unsupervised topic models have found fantastic success in document clustering and classification.
Sparseness-constrained Nonnegative Tensor Factorization for Detecting Topics at Different Time Scales
Further, we propose quantitative ways to measure the topic length and demonstrate the ability of S-NCPD (as well as its online variant) to discover short and long-lasting temporal topics in a controlled manner in semi-synthetic and real-world data including news headlines.
COVID-19 Literature Topic-Based Search via Hierarchical NMF
A dataset of COVID-19-related scientific literature is compiled, combining the articles from several online libraries and selecting those with open access and full text available.
A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression
We present memory-efficient and scalable algorithms for kernel methods used in machine learning.
