When you're trying to get the best performance out of Python, most developers immediately jump to complex algorithmic fixes, using C extensions, or obsessively running profiling tools. However, one of ...

Abstract: We propose a soft gradient boosting framework for sequential regression that embeds a learnable linear feature transform within the boosting procedure. At each boosting iteration, we train a ...

Abstract: In recent years, Machine Learning (ML) models have been introduced across diverse scientific fields, due to their strong predictive performance. However, in many applications the demand for ...