We examine how machine learning can be used to improve and understand human decision-making. In particular, we focus on … released. This is a promising machine learning application because it is a concrete prediction task for which there is a large … volume of data available. Yet comparing the algorithm to the judge proves complicated. First, the data are themselves …

machine learning. We propose a novel adjusted learning algorithm based on peak price tracking for OLPS to tackle this … challenge. The algorithm is based on an aggressive strategy with residual information and transaction costs. We first propose an … adjusted online portfolio selection algorithm using Peak Price Tracking Approach (PPTA) to improve the accuracy of return …

This paper addresses the steep learning curve in Machine Learning faced by noncomputer scientists, particularly social … adage "once you understand OLS, you can work your way up to any other estimator," and apply it to Machine Learning. Focusing … and fire some trailblazers to the forefront of AI and causal machine learning. …