Hyperdimensional computing (HDC) is a biologically-inspired framework wh...
Topological data analysis (TDA) is a powerful technique for extracting
c...
We study randomized matrix-free quadrature algorithms for spectrum and
s...
Learning data representations under uncertainty is an important task tha...
The boundary operator is a linear operator that acts on a collection of
...
We present distributed algorithms for training dynamic Graph Neural Netw...
Quantum computing offers the potential of exponential speedups for certa...
The cumulative empirical spectral measure (CESM) Φ[𝐀] :
ℝ→ [0,1] of a n×...
In recent years, a variety of randomized constructions of sketching matr...
This paper considers the problem of updating the rank-k truncated Singul...
In this study, we address three important challenges related to the COVI...
In modern multilabel classification problems, each data instance belongs...
Many irregular domains such as social networks, financial transactions,
...
High dimensional data and systems with many degrees of freedom are often...
We propose and investigate two new methods to approximate f( A) b
for la...
In this work, we present theoretical results on the convergence of non-c...
This paper addresses matrix approximation problems for matrices that are...
The increasing size and complexity of scientific data could dramatically...