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 algorithm for safer machine learning with different testing and training distributions.
In this work, we extend some quantities introduced in "Optimization of conditional value-at-risk" of R.T Rockafellar and S. Uryasev to the case where the proximity between real numbers is measured by using a Bregman divergence. This leads to the definition of the Bregman superquantile. Axioms of a coherent measure of r…
A federated learning framework using superquantile aggregation for robust performance across heterogeneous data.
A new federated learning framework for handling device heterogeneity.
Conditional Value-at-Risk (CVaR) and Value-at-Risk (VaR), also called the superquantile and quantile, are frequently used to characterize the tails of probability distribution's and are popular measures of risk. Buffered Probability of Exceedance (bPOE) is a recently introduced characterization of the tail which is the…
This paper extends the Risk Quadrangle framework for risk management and optimization.
The paper examines expectile quadrangle properties in risk management.
Unified framework TERM improves fairness and robustness.