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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.OC2026
Sharp Optimal Algorithm for Derivative-Free Stochastic Convex Optimization in One Dimension
Alexandra Carpentier, Chloé Rouyer, Alexandre Tsybakov +1
Stochastic convex optimization is a classical problem with well-understood guarantees under first-order feedback. In contrast, for zero-order optimization with noisy function evalu…
math.ST2026
Gradient-free stochastic optimization of derivatives under strong convexity
Arya Akhavan, Sirine Louati, Alexandre B. Tsybakov
We consider the problem of minimizing the -th order partial derivative of an unknown function along a fixed coordinate direction , based on noisy queri…