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 ...

Abstract: In many engineering applications, the level of nonlinear distortions in frequency response function (FRF) measurements is quantified using specially designed periodic excitation signals ...

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 ...

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 ...

Catalyst is a PyTorch framework for Deep Learning Research and Development. It focuses on reproducibility, rapid experimentation, and codebase reuse so you can create something new rather than write ...