The self-attention mechanism is the key to the success of transformers in recent Large
Language Models (LLMs). However, the quadratic computational cost $ O (n^ 2) $ in the …

The Applied and Numerical Harmonic Analysis (ANHA) book series aims to provide the
engineering, mathematical, and scientific communities with significant developments in …

At the core of many sensing and imaging applications, the signal of interest can be modeled
as a linear superposition of translated or modulated versions of some template [eg, a point …

The problem of imaging point objects can be formulated as estimation of an unknown atomic
measure from its M+ 1 consecutive noisy Fourier coefficients. The standard resolution of this …

In the evolving landscape of machine learning, a pivotal challenge lies in deciphering the
internal representations harnessed by neural networks and Transformers. Building on recent …

We consider the problem of recovering a signal consisting of a superposition of point
sources from low-resolution data with a cutoff frequency. If the distance between the sources …

Analytic continuation is a central step in the simulation of finite-temperature field theories in
which numerically obtained Matsubara data are continued to the real frequency axis for a …

This book bridges theoretical computer science and machine learning by exploring what the
two sides can teach each other. It emphasizes the need for flexible, tractable models that …

We consider the problem of stable recovery of sparse signals of the form from their spectral
measurements, known in a bandwidth with absolute error not exceeding. We consider the …

Accurate knowledge of initial complex excitation coefficients for phased-array elements is
essential to ensure accurate array performance. In the literature, many array calibration …