Fetching the paper…
Reading the bibliography…
A geometric graph associated with a set of points $P= \{x_1, x_2, \cdots, x_n \} \subset \mathbb{R}^d$ and a fixed kernel function $\mathsf{K}:\mathbb{R}^d\times \mathbb{R}^d\to\mathbb{R}_{\geq 0}$ is a complete graph on $P$ such that the weight of edge $(x_i, x_j)$ is $\mathsf{K}(x_i, x_j)$.
Extensions of lipschitz mappings into a hilbert space
William B Johnson and Joram Lindenstrauss · 1984
Earlier work this paper cites.
A decomposition of multidimensional point sets with applications to k k -nearest-neighbors and n n -body potential fields
Paul B. Callahan and S. Rao Kosaraju · 1995
Earlier work this paper cites.
On spectral clustering: Analysis and an algorithm
Andrew Y Ng, Michael I Jordan, and Yair Weiss · 2002
Earlier work this paper cites.
An elementary proof of a theorem of johnson and lindenstrauss
Sanjoy Dasgupta and Anupam Gupta · 2003
Earlier work this paper cites.
Dynamic well-separated pair decomposition made easy
John Fischer and Sariel Har-Peled · 2005
Earlier work this paper cites.
Semi-supervised learning with graphs
Xiaojin Zhu · 2005
Earlier work this paper cites.
Semi-supervised learning literature survey
Xiaojin Jerry Zhu · 2005
Earlier work this paper cites.
A tutorial on spectral clustering, 2007
Ulrike von Luxburg · 2007
Earlier work this paper cites.
N-body simulations (gravitational)
Michele Trenti and Piet Hut · 2008
Earlier work this paper cites.
Gaussian processes for machine learning (gpml) toolbox
Carl Edward Rasmussen and Hannes Nickisch · 2010
Cited alongside, same era.
Geometric approximation algorithms
Sariel Har-Peled · 2011
Cited alongside, same era.
Graph sparsification by effective resistances
Daniel A Spielman and Nikhil Srivastava · 2011
Cited alongside, same era.
Fast randomized kernel ridge regression with statistical guarantees
Ahmed Alaoui and Michael W Mahoney · 2015
Cited alongside, same era.
On fully dynamic graph sparsifiers
Ittai Abraham, David Durfee, Ioannis Koutis, Sebastian Krinninger, and Richard Peng · 2016
Cited alongside, same era.
Federated learning: Strategies for improving communication efficiency
Jakub Konečnỳ, H Brendan McMahan, Felix X Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon · 2016
Solving linear programs in the current matrix multiplication time
Michael B Cohen, Yin Tat Lee, and Zhao Song · 2019
Later among the works it cites.
A unified framework for data poisoning attack to graph-based semi-supervised learning
Xuanqing Liu, Si Si, Xiaojin Zhu, Yang Li, and Cho-Jui Hsieh · 2019
Later among the works it cites.
Algorithms and hardness for linear algebra on geometric graphs
Josh Alman, Timothy Chu, Aaron Schild, and Zhao Song · 2020
Later among the works it cites.
Generalized leverage score sampling for neural networks
Jason D Lee, Ruoqi Shen, Zhao Song, Mengdi Wang, and Zheng Yu · 2020
Later among the works it cites.
Efficiently modeling long sequences with structured state spaces
Albert Gu, Karan Goel, and Christopher Ré · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Sharper bounds for regularized data fitting
Haim Avron, Kenneth L Clarkson, and David P Woodruff · 2017
Cited alongside, same era.
Random fourier features for kernel ridge regression: Approximation bounds and statistical guarantees
Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, and Amir Zandieh · 2017
Cited alongside, same era.
Dynamic minimum spanning forest with subpolynomial worst-case update time
Danupon Nanongkai, Thatchaphol Saranurak, and Christian Wulff-Nilsen · 2017
Cited alongside, same era.
Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, and Christopher Ré · 2021
Later among the works it cites.
Solving sdp faster: A robust ipm framework and efficient implementation, 2021
Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao, and Ruizhe Zhang · 2021
Later among the works it cites.
Faster dynamic matrix inverse for faster lps
Shunhua Jiang, Zhao Song, Omri Weinstein, and Hengjie Zhang · 2021
Later among the works it cites.
A faster interior-point method for sum-of-squares optimization, 2022
Shunhua Jiang, Bento Natura, and Omri Weinstein · 2022
Closest in time.