Tree-based machine learning techniques, such as Decision Trees and Random Forests, are
top performers in several domains as they do well with limited training datasets and offer …

ReRAM-based accelerators have shown great potential for accelerating DNN inference
because ReRAM crossbars can perform analog matrix-vector multiplication operations with low …

Artificial intelligence will be deployed increasingly in more systems that affect public health,
safety, and welfare. These systems will better utilize scarce resources; prevent disasters; and …

… , Yan Fyodorov, Sergey Oblezin and Guillaume Dubach. I thank Sergey Oblezin for inviting
… I thank my brother Sergey for visiting me in Brighton. I further would like to thank my friends …

Structured, or tabular, data is the most common format in data science. While deep learning
models have proven formidable in learning from unstructured data such as images or speech…

Memristors, Flash, and related nonvolatile analog device technologies offer in‐memory
computing structures operating in the analog domain, such as accelerating linear matrix …

Transformer models represent the cutting edge of Deep Neural Networks (DNNs) and excel
in a wide range of machine learning tasks. However, processing these models demands …

Peer-to-Peer (P2P) computing, a novel paradigm for distributed information technology, is
currently receiving ever increasing interest from both academia and industry. Recent efforts …

Deep learning for time series is an emerging area with close ties to industry, yet under
represented in performance benchmarks for machine learning systems. In this paper, we present …

In the work the composite on the basis of fluoroplastic with filler WO 3 is studied and its efficiency
for protection against X-ray and gamma radiation is proved. The technological scheme …