[no abstract available]

Neural network quantization aims to accelerate and trim full-precision neural models by using low bit approximations. Methods adopting the aware training (QAT) paradigm have recently seen a rapid growth, but are often conceptually complicated. This paper proposes novel highly effective QAT method, quantized feature distillation (QFD). QFD first trains (or binarized) representation as teacher, t...

Qat (Catha edulis, Celastraceae) is a woody evergreen species with great economic and cultural importance. It is cultivated for its stimulant alkaloids cathine and cathinone in East Africa and southwest Arabia. However, genome information, especially DNA sequence resources, for C. edulis are limited, hindering studies regarding interspecific and intraspecific relationships. Herein, the complete...

Quantized neural networks (QNNs) are widely used to achieve computationally efficient solutions recognition problems. Overall, eight-bit QNNs have almost the same accuracy as full-precision networks, but working several times faster. However, with lower quantization levels demonstrate inferior in comparison their classical analogs. To solve this issue, a number of quantization-aware training (Q...

A special class of immunologic cells can lyse or damage a variety of target cells, notably malignant cells in vitro. These cells have been called natural killer (NK) cells because lysis does not require deliberate immunization by tumor cells. Although these cells can be distinguished from conventional T cells, B cells, and phagocytic cells, they have been difficult to define. We describe a repr...