A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...

Abstract: We consider the problem of parsimoniously selecting sensors or scheduling sensor observation actions to optimize the covariance of a predicted system state. In contrast to previous work on ...

While experimentation is essential, traditional A/B testing can be excessively slow and expensive, according to DoorDash engineers Caixia Huang and Alex Weinstein. To address these limitations, they ...

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Gordon Scott has been an active investor and ...

Getting AI governance right is one of the most consequential challenges of our time, calling for mutual learning based on the lessons and good practices emerging from the different jurisdictions ...

Casey Murphy has fanned his passion for finance through years of writing about active trading, technical analysis, market commentary, exchange-traded funds (ETFs), commodities, futures, options, and ...

Abstract: Deep Reinforcement Learning (DRL) approaches with Attention Mechanism have shown efficiency and effectiveness for combinatorial optimization problem, such as routing problem for autonomous ...

Note: All implementations are based on published papers and publicly available code. Contributions and corrections are welcome via PR.