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A constrained version of the online convex optimization (OCO) problem is considered. With slotted time, for each slot, first an action is chosen. Subsequently the loss function and the constraint violation penalty evaluated at the chosen…

Machine Learning · Computer Science 2023-01-25 Rahul Vaze

This article concerns the performance limits of strictly causal state estimation for linear systems with fixed, but uncertain, parameters belonging to a finite set. In particular, we provide upper and lower bounds on the smallest achievable…

Optimization and Control · Mathematics 2024-03-29 Olle Kjellqvist

In this paper, we study the pricing of contingent claims under G-expectation. In order to accomodate volatility uncertainty, the price of the risky security is supposed to governed by a general linear stochastic differential equation (SDE)…

Probability · Mathematics 2013-03-19 Mingshang Hu , Shaolin Ji

We examine fixed-price mechanisms in bilateral trade through the lens of regret minimization. Our main results are twofold. (i) For independent values, a near-optimal $\widetilde{\Theta}(T^{2/3})$ tight bound for $\textsf{Global Budget…

Computer Science and Game Theory · Computer Science 2026-05-20 Houshuang Chen , Yaonan Jin , Pinyan Lu , Chihao Zhang

In mathematical modelling, the data and solutions are represented as measurable functions and their quality is oftentimes captured by the membership to a certain function space. One of the core questions for an analysis of a model is the…

Functional Analysis · Mathematics 2022-11-22 Vít Musil , Luboš Pick , Jakub Takáč

Conditional risk minimization arises in high-stakes decisions where risk must be assessed in light of side information, such as stressed economic conditions, specific customer profiles, or other contextual covariates. Constructing reliable…

Machine Learning · Statistics 2025-09-30 Xinqiao Xie , Jonathan Yu-Meng Li

We consider the worst-case expectation of a permutation invariant ambiguity set of discrete distributions as a proxy-cost for data-driven expected risk minimization. For this framework, we coin the term ordered risk minimization to…

Optimization and Control · Mathematics 2023-09-19 Peter Coppens , Panagiotis Patrinos

We study the power and limitations of posted prices in multi-unit markets, where agents arrive sequentially in an arbitrary order. We prove upper and lower bounds on the largest fraction of the optimal social welfare that can be guaranteed…

Computer Science and Game Theory · Computer Science 2020-02-18 Tomer Ezra , Michal Feldman , Tim Roughgarden , Warut Suksompong

We investigate constrained optimal control problems for linear stochastic dynamical systems evolving in discrete time. We consider minimization of an expected value cost over a finite horizon. Hard constraints are introduced first, and then…

Optimization and Control · Mathematics 2011-07-07 Eugenio Cinquemani , Mayank Agarwal , Debasish Chatterjee , John Lygeros

We review some features of topology optimization with a lower bound on the critical load factor, as computed by linearized buckling analysis. The change of the optimized design, the competition between stiffness and stability requirements…

Numerical Analysis · Mathematics 2018-09-25 Federico Ferrari , Ole Sigmund

We show that coherent risk measures are ineffective in curbing the behaviour of investors with limited liability or excessive tail-risk seeking behaviour if the market admits statistical arbitrage opportunities which we term…

Risk Management · Quantitative Finance 2020-10-21 John Armstrong , Damiano Brigo

The classical discrete time model of proportional transaction costs relies on the assumption that a feasible portfolio process has solvent increments at each step. We extend this setting in two directions, allowing for convex transaction…

Mathematical Finance · Quantitative Finance 2021-01-15 Emmanuel Lepinette , Ilya Molchanov

Large learning rates, when applied to gradient descent for nonconvex optimization, yield various implicit biases including the edge of stability (Cohen et al., 2021), balancing (Wang et al., 2022), and catapult (Lewkowycz et al., 2020).…

Machine Learning · Computer Science 2023-12-13 Yuqing Wang , Zhenghao Xu , Tuo Zhao , Molei Tao

Posted price mechanisms are prevalent in allocating goods within online marketplaces due to their simplicity and practical efficiency. We explore a fundamental scenario where buyers' valuations are independent and identically distributed,…

Computer Science and Game Theory · Computer Science 2025-05-26 José Correa , Vasilis Livanos , Dana Pizarro , Victor Verdugo

The regret bound of an optimization algorithms is one of the basic criteria for evaluating the performance of the given algorithm. By inspecting the differences between the regret bounds of traditional algorithms and adaptive one, we…

Machine Learning · Statistics 2017-07-07 HyoungSeok Kim , JiHoon Kang , WooMyoung Park , SukHyun Ko , YoonHo Cho , DaeSung Yu , YoungSook Song , JungWon Choi

Risk measures for multivariate financial positions are studied in a utility-based framework. Under a certain incomplete preference relation, shortfall and divergence risk measures are defined as the optimal values of specific set…

Risk Management · Quantitative Finance 2017-09-12 Çağın Ararat , Andreas H. Hamel , Birgit Rudloff

We address the problem of estimating the expected shortfall risk of a financial loss using a finite number of i.i.d. data. It is well known that the classical plug-in estimator suffers from poor statistical performance when faced with…

Risk Management · Quantitative Finance 2026-02-13 Daniel Bartl , Stephan Eckstein

This paper develops a model for option market making in which the hedging activity of the market maker generates price impact on the underlying asset. The option order flow is modeled by Cox processes, with intensities depending on the…

Trading and Market Microstructure · Quantitative Finance 2026-04-30 Paulin Aubert , Etienne Chevalier , Vathana Ly Vath

Boundary value problems for second-order elliptic equations in divergence form, whose nonlinearity is governed by a convex function of non-necessarily power type, are considered. The global boundedness of their solutions is established…

Analysis of PDEs · Mathematics 2022-07-18 Giuseppina Barletta , Andrea Cianchi , Greta Marino

Distributionally robust chance constrained programs minimize a deterministic cost function subject to the satisfaction of one or more safety conditions with high probability, given that the probability distribution of the uncertain problem…

Optimization and Control · Mathematics 2022-11-22 Zhi Chen , Daniel Kuhn , Wolfram Wiesemann
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