MISSION: Ultra Large-Scale Feature Selection using Count-Sketches

MISSION: Ultra Large-Scale Feature Selection using Count-Sketches

12 June 2018

Amirali Aghazadeh

Gautam Dasarathy

Anshumali Shrivastava

Richard G. Baraniuk

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Papers citing "MISSION: Ultra Large-Scale Feature Selection using Count-Sketches"

9 / 9 papers shown

Title
Improved Frequency Estimation Algorithms with and without Predictions Anders Aamand Justin Y. Chen Huy Le Nguyen Sandeep Silwal A. Vakilian 109 7 0 12 Dec 2023
Asymptotically free sketched ridge ensembles: Risks, cross-validation, and tuning Filip Szatkowski Daniel LeJeune 77 10 0 06 Oct 2023
Scalable variable selection for two-view learning tasks with projection operators S. Szedmák Riikka Huusari Tat Hong Duong Le Juho Rousu 51 1 0 04 Jul 2023
Federated Gradient Matching Pursuit Halyun Jeong Deanna Needell Jing Qin FedML 80 1 0 20 Feb 2023
Asymptotics of the Sketched Pseudoinverse Daniel LeJeune Pratik V. Patil Hamid Javadi Richard G. Baraniuk Robert Tibshirani 54 10 0 07 Nov 2022
On the Robustness of CountSketch to Adaptive Inputs E. Cohen Xin Lyu Jelani Nelson Tamas Sarlos M. Shechner Uri Stemmer AAML 49 22 0 28 Feb 2022
CountSketches, Feature Hashing and the Median of Three Kasper Green Larsen Rasmus Pagh Jakub Tvetek 47 9 0 03 Feb 2021
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders Zahra Atashgahi Ghada Sokar T. Lee Elena Mocanu Decebal Constantin Mocanu Raymond N. J. Veldhuis Mykola Pechenizkiy 94 42 0 01 Dec 2020
Compressing Gradient Optimizers via Count-Sketches Ryan Spring Anastasios Kyrillidis Vijai Mohan Anshumali Shrivastava 58 36 0 01 Feb 2019