Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring. These methods ...

Seeking to reduce the computing power needed for the widely used dynamic mode decomposition algorithm, a team of researchers in China led by Guo-Ping Guo developed a quantum-classical hybrid algorithm ...

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for static ...

Understand the principles of efficient algorithms for dealing with large scale data sets and be able to select appropriate algorithms for specific problems. Understand and be able to apply the main ...

One July afternoon in 2024, Ryan Williams set out to prove himself wrong. Two months had passed since he’d hit upon a startling discovery about the relationship between time and memory in computing.

The original version of this story appeared in Quanta Magazine. One July afternoon in 2024, Ryan Williams set out to prove himself wrong. Two months had passed since he’d hit upon a startling ...

The general perception among data-centric organizations is that data management technology is progressing linearly. Cloud warehouses, for example, are generally deemed superior to on-premise ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

Financial crime risk is not static. A customer’s risk profile can shift rapidly with new transactions, behaviors, or data. Yet historically, many financial institutions relied on one-time or ...