Zobrazeno 1 - 10
of 6 159
pro vyhledávání: '"Richard, Y."'
Autor:
Chiu, Hong-Ming, Zhang, Richard Y.
We describe how the low-rank structure in an SDP can be exploited to reduce the per-iteration cost of a convex primal-dual interior-point method down to $O(n^{3})$ time and $O(n^{2})$ memory, even at very high accuracies. A traditional difficulty is
Externí odkaz:
http://arxiv.org/abs/2407.14013
Autor:
Chen, Richard Y.
This paper resolves a pivotal open problem on nonparametric inference for nonlinear functionals of volatility matrix. Multiple prominent statistical tasks can be formulated as functionals of volatility matrix, yet a unified statistical theory of gene
Externí odkaz:
http://arxiv.org/abs/2404.00606
Autor:
Zhang, Richard Y.
If a sparse semidefinite program (SDP), specified over $n\times n$ matrices and subject to $m$ linear constraints, has an aggregate sparsity graph $G$ with small treewidth, then chordal conversion will sometimes allow an interior-point method to solv
Externí odkaz:
http://arxiv.org/abs/2306.15288
$K$-means clustering is a widely used machine learning method for identifying patterns in large datasets. Recently, semidefinite programming (SDP) relaxations have been proposed for solving the $K$-means optimization problem, which enjoy strong stati
Externí odkaz:
http://arxiv.org/abs/2305.18436
Non-convex gradient descent is a common approach for estimating a low-rank $n\times n$ ground truth matrix from noisy measurements, because it has per-iteration costs as low as $O(n)$ time, and is in theory capable of converging to a minimax optimal
Externí odkaz:
http://arxiv.org/abs/2305.17224
Autor:
Chiu, Hong-Ming, Zhang, Richard Y.
Adversarial training is well-known to produce high-quality neural network models that are empirically robust against adversarial perturbations. Nevertheless, once a model has been adversarially trained, one often desires a certification that the mode
Externí odkaz:
http://arxiv.org/abs/2211.17244
This paper focuses on complete dictionary learning problem, where the goal is to reparametrize a set of given signals as linear combinations of atoms from a learned dictionary. There are two main challenges faced by theoretical and practical studies
Externí odkaz:
http://arxiv.org/abs/2210.12816
Publikováno v:
Frontiers in Cellular and Infection Microbiology, Vol 14 (2024)
Externí odkaz:
https://doaj.org/article/386c053bd5c2485880fb7e7e96c34d88
The matrix completion problem seeks to recover a $d\times d$ ground truth matrix of low rank $r\ll d$ from observations of its individual elements. Real-world matrix completion is often a huge-scale optimization problem, with $d$ so large that even t
Externí odkaz:
http://arxiv.org/abs/2208.11246