Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Swartworth, William"'
We consider the problem of estimating the spectrum of a symmetric bounded entry (not necessarily PSD) matrix via entrywise sampling. This problem was introduced by [Bhattacharjee, Dexter, Drineas, Musco, Ray '22], where it was shown that one can obta
Externí odkaz:
http://arxiv.org/abs/2411.03227
We introduce a new approach for applying sampling-based sketches to two and three mode tensors. We illustrate our technique to construct sketches for the classical problems of $\ell_0$ sampling and producing $\ell_1$ embeddings. In both settings we a
Externí odkaz:
http://arxiv.org/abs/2406.06735
Autor:
Ghadiri, Mehrdad, Lee, Yin Tat, Padmanabhan, Swati, Swartworth, William, Woodruff, David, Ye, Guanghao
We consider the communication complexity of some fundamental convex optimization problems in the point-to-point (coordinator) and blackboard communication models. We strengthen known bounds for approximately solving linear regression, $p$-norm regres
Externí odkaz:
http://arxiv.org/abs/2403.19146
In this paper we consider the problem of recovering a low-rank Tucker approximation to a massive tensor based solely on structured random compressive measurements. Crucially, the proposed random measurement ensembles are both designed to be compactly
Externí odkaz:
http://arxiv.org/abs/2308.13709
We study benign overfitting in two-layer ReLU networks trained using gradient descent and hinge loss on noisy data for binary classification. In particular, we consider linearly separable data for which a relatively small proportion of labels are cor
Externí odkaz:
http://arxiv.org/abs/2306.09955
Given a symmetric matrix $A$, we show from the simple sketch $GAG^T$, where $G$ is a Gaussian matrix with $k = O(1/\epsilon^2)$ rows, that there is a procedure for approximating all eigenvalues of $A$ simultaneously to within $\epsilon \|A\|_F$ addit
Externí odkaz:
http://arxiv.org/abs/2304.09281
Autor:
Ding, Xiaofu, Dong, Xinyu, McGough, Olivia, Shen, Chenxin, Ulichney, Annie, Xu, Ruiyao, Swartworth, William, Chi, Jocelyn T., Needell, Deanna
Motivated by the problem of identifying potential hierarchical population structure on modern survey data containing a wide range of complex data types, we introduce population-based hierarchical non-negative matrix factorization (PHNMF). PHNMF is a
Externí odkaz:
http://arxiv.org/abs/2209.04968
Recently the "SP" (Stochastic Polyak step size) method has emerged as a competitive adaptive method for setting the step sizes of SGD. SP can be interpreted as a method specialized to interpolated models, since it solves the interpolation equations.
Externí odkaz:
http://arxiv.org/abs/2207.08171
We study the problem of testing whether a symmetric $d \times d$ input matrix $A$ is symmetric positive semidefinite (PSD), or is $\epsilon$-far from the PSD cone, meaning that $\lambda_{\min}(A) \leq - \epsilon \|A\|_p$, where $\|A\|_p$ is the Schat
Externí odkaz:
http://arxiv.org/abs/2204.03782
Autor:
Yaniv, Yotam, Moorman, Jacob D., Swartworth, William, Tu, Thomas, Landis, Daji, Needell, Deanna
The Randomized Kaczmarz method (RK) is a stochastic iterative method for solving linear systems that has recently grown in popularity due to its speed and low memory requirement. Selectable Set Randomized Kaczmarz (SSRK) is an variant of RK that leve
Externí odkaz:
http://arxiv.org/abs/2110.04703