A math whiz as a young man, he later blazed trails, both with his theoretical advances and his advocacy for minority students ...
Mathematicians have considered how to watch every corner of a space—but soccer adds moving players, blocked views and constant action ...
Abstract: More and more time series data appear in various fields, and the prediction of multivariate time series has been the key to solve many industrial problems. Therefore, it is necessary to ...
NP-hardness results indicate that finding exact optima and even sufficiently good approximate optima for worst-case instances of many optimization problems is probably out of reach for polynomial-time ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. You are free to share(copy and redistribute) this ...
The Simulated Bifurcation (SB) algorithm is a fast and highly parallelizable state-of-the-art algorithm for quadratic combinatorial optimization inspired by quantum physics and spins dynamics. It ...
The Poisson lognormal model and variants 1 can be used for a variety of multivariate problems when count data are at play. This package implements efficient variational algorithms to fit such models, ...
This work considers the problem of learning cooperative policies in multi-agent settings with partially observable and non-stationary environments without a communication channel. We focus on ...
The historical pursuit of creating intelligent machines has culminated in the modern era of artificial intelligence. However, the efficacy of AI applications is contingent upon a nuanced understanding ...
Abstract: The binary polarization state analyzer (PSA) made of magnetooptic crystal (MO) rotators is a promising technology for achieving low-cost and high-efficiency state of polarization (SOP) ...
Nature-inspired metaheuristic algorithms are important components of artificial intelligence, and are increasingly used across disciplines to tackle various types of challenging optimization problems.