Robust and Risk-Sensitive Acceleration in Gradient Methods
Mert Gurbuzbalaban, Rutgers
First-order methods such as gradient descent (GD) are foundational in optimization. In unconstrained problems with exact gradients,...
Stochastic Kernel Topologies and Implications for Approximations, Robustness, and Learning
Serdar Yuksel, Queens University
Stochastic kernels represent system models, control policies, and measurement channels, and thus offer a general mathematical framework. We...
2026 Byrne Conference on Stochastic Analysis in Finance and Insurance
Attendance is free, but online registration is required for all attendees who are not speakers....
2026 Byrne Conference on Stochastic Analysis in Finance and Insurance
Attendance is free, but online registration is required for all attendees who are not speakers....
2026 Byrne Conference on Stochastic Analysis in Finance and Insurance
Attendance is free, but online registration is required for all attendees who are not speakers....
