To address this problem, an efficient network is proposed for SAR imaging under sparse sampling conditions, which can be designed by an improved conjugate gradient (CG) optimization strategy. First, ...

Software product for analysis of activations and specialization in artificial neural networks (ANN), including spiking neural networks (SNN), with the tensor train (TT) decomposition and other ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6221021 ...

This research project addresses critical challenges in Federated Learning (FL), specifically focusing on: ...

Quantum computing made significant strides in 2024, but it's yet to demonstrate a practical advantage over classical digital ...

Universal Transformer Memory uses neural networks to determine which tokens in the LLM's context window are useful or redundant.

This challenge grows as new tasks arise and models evolve rapidly, making manual methods for prompt engineering increasingly unsustainable. The question then becomes: How can we make prompt ...

In the research, they model the message adversary training process as a cooperative MARL problem, where each adversary ...

Retail sales forecasting has long been a cornerstone of operational success in the industry, guiding businesses in optimizing ...

S&P Global Market Intelligence, a provider of information services and solutions to global markets, today announced the addition of 4.6 million municipal securities on the flagship S&P Capital IQ Pro ...