Recent advances in machine learning are finding commercial applications across many
industries, not least the finance industry. This paper focuses on applications in one of the …

The Multi-Armed Bandit (MAB) is a fundamental model capturing the dilemma between
exploration and exploitation in sequential decision making. At every time step, the decision …

Human-AI complementarity is important when neither the algorithm nor the human yields
dominant performance across all instances in a given context. Recent work that explored …

Sharpe Ratio (SR) is a critical parameter in characterizing financial time series as it jointly
considers the reward and the volatility of any stock/portfolio through its variance. Deriving …

This note considers the model of “constrained multi-armed bandit”(CMAB) that generalizes
that of the classical stochastic MAB by adding a feasibility constraint for each action. The …

This thesis addresses the problem of fraud detection and credit risk from a cost sensitive
perspective, exploring techniques that maximize the benefits to a financial institution while …

Data Mining–known as the process of extracting knowledge from massive data sets–leads to
phenomenal impacts on our society, and now affects nearly every aspect of our lives: from …

This thesis divides into two parts: the first part is on ranking and the second on risk-aware
reinforcement learning. While binary classification is the flagship application of empirical risk …

IDEMIA is the leading company in biometric identification and security, as well as secure
payments. The company is a merger of the companies Morpho and Oberthur Technologies …

This study investigates how modern machine learning (ML) techniques can be used to
advance the field of quantitative investing. A broad literature review evaluated the common …