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08/01/2023
Harnessing the Power of Sample Abundance: Theoretical Guarantees and Algorithms for Accelerated One-Bit Sensing
One-bit quantization with time-varying sampling thresholds (also known a...
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07/08/2023
Manifold Filter-Combine Networks
We introduce a class of manifold neural networks (MNNs) that we call Man...
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06/16/2023
Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign?
We study benign overfitting in two-layer ReLU networks trained using gra...
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06/07/2023
Stochastic Natural Thresholding Algorithms
Sparse signal recovery is one of the most fundamental problems in variou...
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06/01/2023
Curvature corrected tangent space-based approximation of manifold-valued data
When generalizing schemes for real-valued data approximation or decompos...
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05/23/2023
Detecting and Mitigating Indirect Stereotypes in Word Embeddings
Societal biases in the usage of words, including harmful stereotypes, ar...
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05/06/2023
Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruption
We study the tensor robust principal component analysis (TRPCA) problem,...
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04/20/2023
Linear Convergence of Reshuffling Kaczmarz Methods With Sparse Constraints
The Kaczmarz method (KZ) and its variants, which are types of stochastic...
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03/16/2023
One-Bit Quadratic Compressed Sensing: From Sample Abundance to Linear Feasibility
One-bit quantization with time-varying sampling thresholds has recently ...
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02/28/2023
Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling
We introduce a new method based on nonnegative matrix factorization, Neu...
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02/20/2023
Federated Gradient Matching Pursuit
Traditional machine learning techniques require centralizing all trainin...
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12/23/2022
A Convergence Rate for Manifold Neural Networks
High-dimensional data arises in numerous applications, and the rapidly d...
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12/19/2022
Continuous Semi-Supervised Nonnegative Matrix Factorization
Nonnegative matrix factorization can be used to automatically detect top...
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12/07/2022
Multi-Randomized Kaczmarz for Latent Class Regression
Linear regression is effective at identifying interpretable trends in a ...
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12/01/2022
Inference of Media Bias and Content Quality Using Natural-Language Processing
Media bias can significantly impact the formation and development of opi...
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11/24/2022
Multi-scale Hybridized Topic Modeling: A Pipeline for Analyzing Unstructured Text Datasets via Topic Modeling
We propose a multi-scale hybridized topic modeling method to find hidden...
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11/11/2022
Online Signal Recovery via Heavy Ball Kaczmarz
Recovering a signal x^∗∈ℝ^n from a sequence of linear measurements is an...
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11/10/2022
Sketched Gaussian Model Linear Discriminant Analysis via the Randomized Kaczmarz Method
We present sketched linear discriminant analysis, an iterative randomize...
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09/12/2022
Population-Based Hierarchical Non-negative Matrix Factorization for Survey Data
Motivated by the problem of identifying potential hierarchical populatio...
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08/28/2022
Automatic Infectious Disease Classification Analysis with Concept Discovery
Automatic infectious disease classification from images can facilitate n...
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08/20/2022
Matrix Completion with Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling
While uniform sampling has been widely studied in the matrix completion ...
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08/17/2022
Geometric Scattering on Measure Spaces
The scattering transform is a multilayered, wavelet-based transform init...
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07/17/2022
SP2: A Second Order Stochastic Polyak Method
Recently the "SP" (Stochastic Polyak step size) method has emerged as a ...
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06/25/2022
On Block Accelerations of Quantile Randomized Kaczmarz for Corrupted Systems of Linear Equations
With the growth of large data as well as large-scale learning tasks, the...
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06/21/2022
The Manifold Scattering Transform for High-Dimensional Point Cloud Data
The manifold scattering transform is a deep feature extractor for data d...
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04/08/2022
Testing Positive Semidefiniteness Using Linear Measurements
We study the problem of testing whether a symmetric d × d input matrix A...
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02/28/2022
Distributed randomized Kaczmarz for the adversarial workers
Developing large-scale distributed methods that are robust to the presen...
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02/28/2022
Semi-supervised Nonnegative Matrix Factorization for Document Classification
We propose new semi-supervised nonnegative matrix factorization (SSNMF) ...
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01/31/2022
Guided Semi-Supervised Non-negative Matrix Factorization on Legal Documents
Classification and topic modeling are popular techniques in machine lear...
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10/10/2021
Selectable Set Randomized Kaczmarz
The Randomized Kaczmarz method (RK) is a stochastic iterative method for...
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10/07/2021
On audio enhancement via online non-negative matrix factorization
We propose a method for noise reduction, the task of producing a clean a...
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09/30/2021
A Generalized Hierarchical Nonnegative Tensor Decomposition
Nonnegative matrix factorization (NMF) has found many applications inclu...
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09/28/2021
Robust recovery of bandlimited graph signals via randomized dynamical sampling
Heat diffusion processes have found wide applications in modelling dynam...
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09/21/2021
Modewise Operators, the Tensor Restricted Isometry Property, and Low-Rank Tensor Recovery
Recovery of sparse vectors and low-rank matrices from a small number of ...
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08/23/2021
Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition
We study the problem of tensor robust principal component analysis (TRPC...
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08/04/2021
QuantileRK: Solving Large-Scale Linear Systems with Corrupted, Noisy Data
Measurement data in linear systems arising from real-world applications ...
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07/19/2021
Analysis of Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data
We develop a method for analyzing spatiotemporal anomalies in geospatial...
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05/19/2021
Statistical Learning for Best Practices in Tattoo Removal
The causes behind complications in laser-assisted tattoo removal are cur...
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04/28/2021
Analysis of Legal Documents via Non-negative Matrix Factorization Methods
The California Innocence Project (CIP), a clinical law school program ai...
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03/19/2021
Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions
Low rank tensor approximation is a fundamental tool in modern machine le...
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01/05/2021
Robust CUR Decomposition: Theory and Imaging Applications
This paper considers the use of Robust PCA in a CUR decomposition framew...
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11/10/2020
Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data
Online nonnegative matrix factorization (ONMF) is a matrix factorization...
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10/22/2020
On a Guided Nonnegative Matrix Factorization
Fully unsupervised topic models have found fantastic success in document...
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10/15/2020
Semi-supervised NMF Models for Topic Modeling in Learning Tasks
We propose several new models for semi-supervised nonnegative matrix fac...
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10/04/2020
On Nonnegative Matrix and Tensor Decompositions for COVID-19 Twitter Dynamics
We analyze Twitter data relating to the COVID-19 pandemic using dynamic ...
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09/17/2020
Quantile-based Iterative Methods for Corrupted Systems of Linear Equations
Often in applications ranging from medical imaging and sensor networks t...
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09/16/2020
Online nonnegative tensor factorization and CP-dictionary learning for Markovian data
Nonnegative Matrix Factorization (NMF) algorithms are fundamental tools ...
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09/07/2020
COVID-19 Literature Topic-Based Search via Hierarchical NMF
A dataset of COVID-19-related scientific literature is compiled, combini...
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08/24/2020
Feature Selection on Lyme Disease Patient Survey Data
Lyme disease is a rapidly growing illness that remains poorly understood...
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07/30/2020