Ising machines are hardware solvers that aim to find the absolute or approximate ground
states of the Ising model. The Ising model is of fundamental computational interest because …

In recent years, the limits of the multicore approach emerged in the so-called “dark silicon”
issue and diminishing returns of an ever-increasing core count. Hardware manufacturers …

Deep neural networks have been applied in many applications exhibiting extraordinary
abilities in the field of computer vision. However, complex network architectures challenge …

Deep learning's recent history has been one of achievement: from triumphing over humans
in the game of Go to world-leading performance in image classification, voice recognition …

New machine learning accelerators are being announced and released each month for a
variety of applications from speech recognition, video object detection, assisted driving, and …

Analog hardware accelerators, which perform computation within a dense memory array,
have the potential to overcome the major bottlenecks faced by digital hardware for data …

The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors
has brought on new opportunities for applying both Deep and Spiking Neural Network …

Over the past several years, new machine learning accelerators were being announced and
released every month for a variety of applications from speech recognition, video object …

Computers have undergone tremendous improvements in performance over the last 60
years, but those improvements have significantly slowed down over the last decade, owing …

The increasing demand for high-resolution hyperspectral images from nano and
microsatellites conflicts with the strict bandwidth constraints for downlink transmission. A …