Spread Spectrum for Universal Compressive Sampling

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An integer program (IP) is a problem of the form

\min \{f(x) : \, Ax = b, \ l \leq x \leq u, \ x \in \Z^n\}

, where

A \in \Z^{m \times n}

b \in \Z^m

l,u \in \Z^n

, and

f: \Z^n \rightarrow \Z

is a separable convex objective function. The problem o ...

Based on the spectral divide-and-conquer algorithm by Nakatsukasa and Higham [SIAM J. Sci. Comput., 35(3):A1325-A1349, 2013], we propose a new algorithm for computing all the eigenvalues and eigenvectors of a symmetric banded matrix with small bandwidth, w ...

The input of almost every machine learning algorithm targeting the properties of matter at the atomic scale involves a transformation of the list of Cartesian atomic coordinates into a more symmetric representation. Many of the most popular representations ...

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Spread Spectrum for Universal Compressive Sampling

Chat with Graph Search

TimeEvolver: A program for time evolution with improved error bound

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

Unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

Functional estimation of anisotropic covariance and autocovariance operators on the sphere

Statistical limits of dictionary learning: Random matrix theory and the spectral replica method

Efficient Learning of a Linear Dynamical System with Stability Guarantees

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

High-dimensional optimization under nonconvex excluded volume constraints

New Results in Integer and Lattice Programming

A fast spectral divide-and-conquer method for banded matrices

Optimal radial basis for density-based atomic representations

Sub-Matrix Factorization for Real-Time Vote Prediction