activity
20232026
collaborators

10 papers

q-fin.PM2026

Generalizing Markowitz Portfolio Optimization by a Quadratic Risk Measure

Ignas Gasparavičius, Andrius Grigutis

We show that the key optimization results of the classical Markowitz portfolio selection theory, originally formulated for variance as the risk measure, remain available in explici…

math.PR2026

Self-normalised Bennett inequalities for Hilbert-valued martingales

David Janz

We prove time-uniform self-normalised Bennett inequalities for a martingale in a separable Hilbert space, with and increments bounded in norm by one. Writi…

cs.LG2026

Variance-sensitive Thompson sampling for generalised linear bandits, revisited

Tom Perneczky, Marc Abeille, David Janz

We prove a variance-sensitive regret bound for Thompson sampling in stochastic generalised linear bandits. The argument assumes a warm-up, after which the regret is controlled thro…

cs.LG2026

Sharp analysis of linear ensemble sampling

David Janz, Arya Akhavan, Csaba Szepesvári

We analyse linear ensemble sampling (ES) with standard Gaussian perturbations in stochastic linear bandits. We show that for ensemble size , ES attains $\tilde O(d^{3…

cs.LG2026

Eluder dimension: localise it!

Alireza Bakhtiari, Alex Ayoub, Samuel Robertson +2

We establish a lower bound on the eluder dimension of generalised linear model classes, showing that standard eluder dimension-based analysis cannot lead to first-order regret boun…

cs.LG2025

High-probability zeroth-order online convex optimisation beyond Euclidean geometry

David Janz, El-Mahdi El-Mhamdi, Arya Akhavan

We study online convex optimisation with -Lipschitz losses, -regularised FTRL, and randomised two-point finite-difference gradient estimators based on cone-measure…