no code implementations • 2 Mar 2024 • Halyun Jeong, Deanna Needell, Elizaveta Rebrova
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.
no code implementations • 20 Aug 2022 • Michał Dereziński, Elizaveta Rebrova
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.
no code implementations • 3 Jun 2021 • Elizaveta Rebrova, Yu-Hang Tang
We introduce and investigate matrix approximation by decomposition into a sum of radial basis function (RBF) components.
no code implementations • 28 Apr 2021 • Ryan Budahazy, Lu Cheng, Yihuan Huang, Andrew Johnson, Pengyu Li, Joshua Vendrow, Zhoutong Wu, Denali Molitor, Elizaveta Rebrova, Deanna Needell
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.
1 code implementation • 22 Oct 2020 • Joshua Vendrow, Jamie Haddock, Elizaveta Rebrova, Deanna Needell
Fully unsupervised topic models have found fantastic success in document clustering and classification.
1 code implementation • 4 Oct 2020 • Lara Kassab, Alona Kryshchenko, Hanbaek Lyu, Denali Molitor, Deanna Needell, Elizaveta Rebrova, Jiahong Yuan
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.
no code implementations • EMNLP (NLP-COVID19) 2020 • Rachel Grotheer, Yihuan Huang, Pengyu Li, Elizaveta Rebrova, Deanna Needell, Longxiu Huang, Alona Kryshchenko, Xia Li, Kyung Ha, Oleksandr Kryshchenko
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.
no code implementations • 27 Mar 2018 • Elizaveta Rebrova, Gustavo Chavez, Yang Liu, Pieter Ghysels, Xiaoye Sherry Li
We present memory-efficient and scalable algorithms for kernel methods used in machine learning.