Deanna Needell

research

∙ 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...

0 Arian Eamaz, et al. ∙

research

∙ 07/08/2023

Manifold Filter-Combine Networks

We introduce a class of manifold neural networks (MNNs) that we call Man...

0 Joyce Chew, et al. ∙

research

∙ 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...

0 Erin George, et al. ∙

research

∙ 06/07/2023

Stochastic Natural Thresholding Algorithms

Sparse signal recovery is one of the most fundamental problems in variou...

0 Rachel Grotheer, et al. ∙

research

∙ 06/01/2023

Curvature corrected tangent space-based approximation of manifold-valued data

When generalizing schemes for real-valued data approximation or decompos...

0 Willem Diepeveen, et al. ∙

research

∙ 05/23/2023

Detecting and Mitigating Indirect Stereotypes in Word Embeddings

Societal biases in the usage of words, including harmful stereotypes, ar...

0 Erin George, et al. ∙

research

∙ 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,...

0 HanQin Cai, et al. ∙

research

∙ 04/20/2023

Linear Convergence of Reshuffling Kaczmarz Methods With Sparse Constraints

The Kaczmarz method (KZ) and its variants, which are types of stochastic...

0 Halyun Jeong, et al. ∙

research

∙ 03/16/2023

One-Bit Quadratic Compressed Sensing: From Sample Abundance to Linear Feasibility

One-bit quantization with time-varying sampling thresholds has recently ...

0 Arian Eamaz, et al. ∙

research

∙ 02/28/2023

Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling

We introduce a new method based on nonnegative matrix factorization, Neu...

0 Tyler Will, et al. ∙

research

∙ 02/20/2023

Federated Gradient Matching Pursuit

Traditional machine learning techniques require centralizing all trainin...

0 Halyun Jeong, et al. ∙

research

∙ 12/23/2022

A Convergence Rate for Manifold Neural Networks

High-dimensional data arises in numerous applications, and the rapidly d...

0 Joyce Chew, et al. ∙

research

∙ 12/19/2022

Continuous Semi-Supervised Nonnegative Matrix Factorization

Nonnegative matrix factorization can be used to automatically detect top...

0 Michael R. Lindstrom, et al. ∙

research

∙ 12/07/2022

Multi-Randomized Kaczmarz for Latent Class Regression

Linear regression is effective at identifying interpretable trends in a ...

0 Erin George, et al. ∙

research

∙ 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...

0 Zehan Chao, et al. ∙

research

∙ 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...

0 Keyi Cheng, et al. ∙

research

∙ 11/11/2022

Online Signal Recovery via Heavy Ball Kaczmarz

Recovering a signal x^∗∈ℝ^n from a sequence of linear measurements is an...

0 Benjamin Jarman, et al. ∙

research

∙ 11/10/2022

Sketched Gaussian Model Linear Discriminant Analysis via the Randomized Kaczmarz Method

We present sketched linear discriminant analysis, an iterative randomize...

0 Jocelyn T. Chi, et al. ∙

research

∙ 09/12/2022

Population-Based Hierarchical Non-negative Matrix Factorization for Survey Data

Motivated by the problem of identifying potential hierarchical populatio...

0 Xiaofu Ding, et al. ∙

research

∙ 08/28/2022

Automatic Infectious Disease Classification Analysis with Concept Discovery

Automatic infectious disease classification from images can facilitate n...

0 Elena Sizikova, et al. ∙

research

∙ 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 ...

8 HanQin Cai, et al. ∙

research

∙ 08/17/2022

Geometric Scattering on Measure Spaces

The scattering transform is a multilayered, wavelet-based transform init...

7 Joyce Chew, et al. ∙

research

∙ 07/17/2022

SP2: A Second Order Stochastic Polyak Method

Recently the "SP" (Stochastic Polyak step size) method has emerged as a ...

5 Shuang Li, et al. ∙

research

∙ 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...

0 Lu Cheng, et al. ∙

research

∙ 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...

12 Joyce Chew, et al. ∙

research

∙ 04/08/2022

Testing Positive Semidefiniteness Using Linear Measurements

We study the problem of testing whether a symmetric d × d input matrix A...

0 Deanna Needell, et al. ∙

research

∙ 02/28/2022

Distributed randomized Kaczmarz for the adversarial workers

Developing large-scale distributed methods that are robust to the presen...

0 Xia Li, et al. ∙

research

∙ 02/28/2022

Semi-supervised Nonnegative Matrix Factorization for Document Classification

We propose new semi-supervised nonnegative matrix factorization (SSNMF) ...

5 Jamie Haddock, et al. ∙

research

∙ 01/31/2022

Guided Semi-Supervised Non-negative Matrix Factorization on Legal Documents

Classification and topic modeling are popular techniques in machine lear...

4 Pengyu Li, et al. ∙

research

∙ 10/10/2021

Selectable Set Randomized Kaczmarz

The Randomized Kaczmarz method (RK) is a stochastic iterative method for...

0 Yotam Yaniv, et al. ∙

research

∙ 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...

0 Andrew Sack, et al. ∙

research

∙ 09/30/2021

A Generalized Hierarchical Nonnegative Tensor Decomposition

Nonnegative matrix factorization (NMF) has found many applications inclu...

18 Joshua Vendrow, et al. ∙

research

∙ 09/28/2021

Robust recovery of bandlimited graph signals via randomized dynamical sampling

Heat diffusion processes have found wide applications in modelling dynam...

0 Longxiu Huang, et al. ∙

research

∙ 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 ...

0 Mark A. Iwen, et al. ∙

research

∙ 08/23/2021

Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition

We study the problem of tensor robust principal component analysis (TRPC...

4 HanQin Cai, et al. ∙

research

∙ 08/04/2021

QuantileRK: Solving Large-Scale Linear Systems with Corrupted, Noisy Data

Measurement data in linear systems arising from real-world applications ...

0 Benjamin Jarman, et al. ∙

research

∙ 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...

0 Abigail Hickok, et al. ∙

research

∙ 05/19/2021

Statistical Learning for Best Practices in Tattoo Removal

The causes behind complications in laser-assisted tattoo removal are cur...

0 Richard Yim, et al. ∙

research

∙ 04/28/2021

Analysis of Legal Documents via Non-negative Matrix Factorization Methods

The California Innocence Project (CIP), a clinical law school program ai...

17 Ryan Budahazy, et al. ∙

research

∙ 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...

5 HanQin Cai, et al. ∙

research

∙ 01/05/2021

Robust CUR Decomposition: Theory and Imaging Applications

This paper considers the use of Robust PCA in a CUR decomposition framew...

1 HanQin Cai, et al. ∙

research

∙ 11/10/2020

Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data

Online nonnegative matrix factorization (ONMF) is a matrix factorization...

13 Hanbaek Lyu, et al. ∙

research

∙ 10/22/2020

On a Guided Nonnegative Matrix Factorization

Fully unsupervised topic models have found fantastic success in document...

0 Joshua Vendrow, et al. ∙

research

∙ 10/15/2020

Semi-supervised NMF Models for Topic Modeling in Learning Tasks

We propose several new models for semi-supervised nonnegative matrix fac...

1 Jamie Haddock, et al. ∙

research

∙ 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 ...

0 Lara Kassab, et al. ∙

research

∙ 09/17/2020

Quantile-based Iterative Methods for Corrupted Systems of Linear Equations

Often in applications ranging from medical imaging and sensor networks t...

0 Jamie Haddock, et al. ∙

research

∙ 09/16/2020

Online nonnegative tensor factorization and CP-dictionary learning for Markovian data

Nonnegative Matrix Factorization (NMF) algorithms are fundamental tools ...

7 Christopher Strohmeier, et al. ∙

research

∙ 09/07/2020

COVID-19 Literature Topic-Based Search via Hierarchical NMF

A dataset of COVID-19-related scientific literature is compiled, combini...

0 Rachel Grotheer, et al. ∙

research

∙ 08/24/2020

Feature Selection on Lyme Disease Patient Survey Data

Lyme disease is a rapidly growing illness that remains poorly understood...

0 Joshua Vendrow, et al. ∙

research

∙ 07/30/2020

Random Vector Functional Link Networks for Function Approximation on Manifolds

The learning speed of feed-forward neural networks is notoriously slow a...

5 Deanna Needell, et al. ∙

Deanna Needell

Featured Co-authors