A research team at Duke University has developed a new AI framework that can uncover simple, understandable rules that govern ...

Abstract: We consider the problem of online sparse linear approximation, where a learner sequentially predicts the best sparse linear approximations of an as yet unobserved sequence of measurements in ...

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: Recent years have seen a surging interest in developing under-approximations of reachable sets due to their potential applications in control synthesis and verification. In this letter, we ...

Learn how the Least Squares Criterion determines the line of best fit for data analysis, enhancing predictive accuracy in finance, economics, and investing.

One challenge in large scale data science is that even linear algorithms can result in large data processing cost and long latency, which limit the interactivity of the system and the productivity of ...