Chemists routinely optimize reactions to maximize the yield of their desired products, but understanding why those reactions ...

A machine learning framework combining random forest prediction, neural network defect screening, and evolutionary ...

A new hybrid AI framework combining deep convolutional networks with multi-objective evolutionary optimization achieves 98.5 ...

In a sea of vendors who promise to optimize e-commerce and boost sales, wading through the advertisements to find the right match for the right process can be incredibly difficult. German-based ...

WiMi's proposed technical solution has its core innovations concentrated on the deep integration of model-based reinforcement learning algorithms and hierarchical circuit structures, constructing a ...

Great progress has been made in the past few years in our understanding of nonconvex optimizations. In this talk, I will share with you three of our works in this direction. In one, we study low-rank ...

Supply chains are experiencing a period of significant disruption and challenge that is unlikely to abate in the short term. Covid-19, the war in Ukraine, rising fuel prices and now a looming ...

I'm not sure whether to solve this with generative AI or traditional machine learning.' I receive this inquiry very often these days.I believe the background to this is that 'AI' has come to almost ...

The machine learning market is growing in leaps and bounds, and experts project continued growth. A report by McKinsey indicates that AI has a large potential to be a significant driver of economic ...

Overview:  Deep learning uses multi-layer neural networks to learn patterns from data.CNNs, RNNs, LSTMs, transformers, and ...