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We develop a new continuous-time stochastic gradient descent method for optimizing over the stationary distribution of stochastic differential equation (SDE) models. The algorithm continuously updates the SDE model's parameters using an…

Machine Learning · Computer Science 2023-08-29 Ziheng Wang , Justin Sirignano

Traditionally, systems governed by linear Partial Differential Equations (PDEs) are spatially discretized to exploit their algebraic structure and reduce the computational effort for controlling them. Due to beneficial insights of the PDEs,…

Systems and Control · Computer Science 2016-04-05 Saber Jafarizadeh

Spectral sparsification is a technique that is used to reduce the number of non-zero entries in a positive semidefinite matrix with little changes to its spectrum. In particular, the main application of spectral sparsification is to…

Data Structures and Algorithms · Computer Science 2021-04-13 Fabricio Mendoza-Granada , Marcos Villagra

The paper studies the scenario of wireless multicast with a single transmitter and a relay that deliver scalable source symbols to the receivers in a decode-and-forward (DF) fashion. With the end-to-end mean square error distortion (EED) as…

Information Theory · Computer Science 2017-09-05 Z. Chen , P. Ho , L. Peng

We study subgraphs of Paley graphs of prime order $p$ induced on the sets of vertices extending a given independent set of size $a$ to a larger independent set. Using a sufficient condition proved in the author's recent companion work, we…

Combinatorics · Mathematics 2023-03-30 Dmitriy Kunisky

Einsiedler, Mozes, Shah and Shapira [Compos. Math. 152 (2016), 667-692] prove an equidistribution theorem for rational points on expanding horospheres in the space of d-dimensional Euclidean lattices, with d>2. Their proof exploits measure…

Number Theory · Mathematics 2016-09-05 Min Lee , Jens Marklof

We propose a fast and scalable optimization method to solve chance or probabilistic constrained optimization problems governed by partial differential equations (PDEs) with high-dimensional random parameters. To address the critical…

Optimization and Control · Mathematics 2020-11-20 Peng Chen , Omar Ghattas

A well-designed numerical method for the shallow water equations (SWE) should ensure well-balancedness, nonnegativity of water heights, and entropy stability. For a continuous finite element discretization of a nonlinear hyperbolic system…

Numerical Analysis · Mathematics 2022-07-18 Hennes Hajduk , Dmitri Kuzmin

We study the joint distributions of translated measures supported on leaves which are expanded by subgroups of diagonal matrices and generalize previous results of Kleinbock--Margulis, Dabbs--Kelly--Li, and Shi. More specifically, we…

Dynamical Systems · Mathematics 2021-05-13 Michael Björklund , Alexander Gorodnik

We present a rotation-equivariant unsupervised learning framework for the sparse deconvolution of non-negative scalar fields defined on the unit sphere. Spherical signals with multiple peaks naturally arise in Diffusion MRI (dMRI), where…

Image and Video Processing · Electrical Eng. & Systems 2021-02-19 Axel Elaldi , Neel Dey , Heejong Kim , Guido Gerig

Recently Mohammadi and Salehi-Golsefidy gave necessary and sufficient conditions under which certain translates of homogeneous measures converge, and they determined the limiting measures in the cases of convergence. The class of measures…

Dynamical Systems · Mathematics 2016-04-18 Kathryn Dabbs , Michael Kelly , Han Li

Sparse generalized eigenvalue problem (GEP) plays a pivotal role in a large family of high-dimensional statistical models, including sparse Fisher's discriminant analysis, canonical correlation analysis, and sufficient dimension reduction.…

Machine Learning · Statistics 2018-09-05 Kean Ming Tan , Zhaoran Wang , Han Liu , Tong Zhang

Matrix sketching is a powerful tool for reducing the size of large data matrices. Yet there are fundamental limitations to this size reduction when we want to recover an accurate estimator for a task such as least square regression. We show…

Data Structures and Algorithms · Computer Science 2024-05-10 Sachin Garg , Kevin Tan , Michał Dereziński

A novel class of graphs, here named quasiperiodic, are constructed via application of the Horizontal Visibility algorithm to the time series generated along the quasiperiodic route to chaos. We show how the hierarchy of mode-locked regions…

Chaotic Dynamics · Physics 2015-06-04 Bartolo Luque , Fernando J. Ballesteros , Ángel M. Núñez , Alberto Robledo

Multivariate Time Series Forecasting (MTSF) has long been a key research focus. Traditionally, these studies assume a fixed number of variables, but in real-world applications, Cyber-Physical Systems often expand as new sensors are…

Machine Learning · Computer Science 2025-06-03 Minbo Ma , Kai Tang , Huan Li , Fei Teng , Dalin Zhang , Tianrui Li

Effective String Theory (EST) is a powerful tool used to study confinement in pure gauge theories by modeling the confining flux tube connecting a static quark-anti-quark pair as a thin vibrating string. Recently, flow-based samplers have…

High Energy Physics - Lattice · Physics 2025-01-09 Michele Caselle , Elia Cellini , Alessandro Nada

In regression analysis under artificial neural networks, the prediction performance depends on determining the appropriate weights between layers. As randomly initialized weights are updated during back-propagation using the gradient…

Machine Learning · Computer Science 2020-09-09 Eunho Koo , Hyungjun Kim

A class of discrete probability distributions contains distributions with limited support. A typical example is some variant of a Likert scale, with response mapped to either the $\{1, 2, \ldots, 5\}$ or $\{-3, -2, \ldots, 2, 3\}$ set. An…

Applications · Statistics 2022-04-25 Bogdan Ćmiel , Jakub Nawała , Lucjan Janowski , Krzysztof Rusek

We introduce the directional short-time fractional Fourier transform (DSTFRFT) and prove an extended Parseval's identity and a reconstruction formula for it. We also investigate the continuity of both the directional short-time fractional…

Functional Analysis · Mathematics 2025-09-17 Astrit Ferizi , Katerina Hadzi-Velkova Saneva , Snjezana Maksimovic

The Hubble Frontier Fields represent the opportunity to probe the high-redshift evolution of the main sequence of star-forming galaxies to lower masses than possible in blank fields thanks to foreground lensing of massive galaxy clusters.…

Astrophysics of Galaxies · Physics 2022-08-17 L. Sandles , E. Curtis-Lake , S. Charlot , J. Chevallard , R. Maiolino