A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
New algorithms ensure fair selection in combinatorial semi-bandit with unrestricted delays.
A new learning-to-rank approach ensures fairness for item providers in dynamic ranking systems.
Quantitative analysis of soccer players' passing ability focuses on descriptive statistics without considering the players' real contribution to the passing and ball possession strategy of their team. Which player is able to help the build-up of an attack, or to maintain the possession of the ball? We introduce a novel…
Delegated votes in Uniswap DAO favor parties with less self-owned votes and a16z-affiliated entities.
While implicit feedback (e.g., clicks, dwell times, etc.) is an abundant and attractive source of data for learning to rank, it can produce unfair ranking policies for both exogenous and endogenous reasons. Exogenous reasons typically manifest themselves as biases in the training data, which then get reflected in the l…
This paper tackles fair online decision-making in contextual bandits, achieving optimal performance and fairness.