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In this paper, we investigate an interesting and important stopping problem mixed with stochastic controls and a \textit{nonsmooth} utility over a finite time horizon. The paper aims to develop new methodologies, which are significantly…

Optimization and Control · Mathematics 2015-07-06 Chonghu Guan , Xun Li , Zuoquan Xu , Fahuai Yi

We study the termination problem of the chase algorithm, a central tool in various database problems such as the constraint implication problem, Conjunctive Query optimization, rewriting queries using views, data exchange, and data…

Databases · Computer Science 2009-09-17 Michael Meier , Michael Schmidt , Georg Lausen

We present a general approach to prove existence of solutions for optimal control problems not based on typical convexity conditions which quite often are very hard, if not impossible, to check. By taking advantage of several relaxations of…

Optimization and Control · Mathematics 2014-01-21 Pablo Pedregal , Jorge Tiago

We develop an approach for solving one-sided optimal stopping problems in discrete time for general underlying Markov processes on the real line. The main idea is to transform the problem into an auxiliary problem for the ladder height…

Probability · Mathematics 2018-10-29 Sören Christensen , Albrecht Irle

This paper proposes a new indirect solution method for solving state-constrained optimal control problems by revisiting the well-established optimal control theory and addressing the long-standing issue of discontinuous control and costate…

Optimization and Control · Mathematics 2024-03-08 Kenshiro Oguri

Motivated by studies of indirect measurements in quantum mechanics, we investigate stochastic differential equations with a fixed point subject to an additional infinitesimal repulsive perturbation. We conjecture, and prove for an important…

Mathematical Physics · Physics 2018-07-18 Michel Bauer , Denis Bernard

We study batched bandit experiments and consider the problem of inference conditional on the realized stopping time, assignment probabilities, and target parameter, where all of these may be chosen adaptively using information up to the…

Methodology · Statistics 2026-01-21 Jiafeng Chen , Isaiah Andrews

Nash equilibrium is a popular solution concept for solving imperfect-information games in practice. However, it has a major drawback: it does not preclude suboptimal play in branches of the game tree that are not reached in equilibrium.…

Computer Science and Game Theory · Computer Science 2017-05-29 Christian Kroer , Gabriele Farina , Tuomas Sandholm

In this paper, we investigate infinite horizon jump-diffusion forward-backward stochastic differential equations under some monotonicity conditions. We establish an existence and uniqueness theorem, two stability results and a comparison…

Probability · Mathematics 2016-08-22 Zhiyong Yu

Continual learning from streaming data sources becomes more and more popular due to the increasing number of online tools and systems. Dealing with dynamic and everlasting problems poses new challenges for which traditional batch-based…

Machine Learning · Computer Science 2020-09-22 Łukasz Korycki , Bartosz Krawczyk

The piecewise-stationary bandit problem is an important variant of the multi-armed bandit problem that further considers abrupt changes in the reward distributions. The main theme of the problem is the trade-off between exploration for…

Machine Learning · Computer Science 2024-10-10 Kuan-Ta Li , Ping-Chun Hsieh , Yu-Chih Huang

We study a boundary-value quasilinear elliptic problem on a generic time scale. Making use of the fixed-point index theory, sufficient conditions are given to obtain existence, multiplicity, and infinite solvability of positive solutions.

Analysis of PDEs · Mathematics 2007-10-08 Moulay Rchid Sidi Ammi , Delfim F. M. Torres

We consider global optimization problems, where the feasible region $\X$ is a compact subset of $\mathbb{R}^d$ with $d \geq 10$. For these problems, we demonstrate the following. First: the actual convergence of global random search…

Optimization and Control · Mathematics 2023-02-27 Jack Noonan , Anatoly Zhigljavsky

We develop sufficient conditions for the existence of the weak sharp minima at infinity property for nonsmooth optimization problems via asymptotic cones and generalized asymptotic functions. Next, we show that these conditions are also…

Optimization and Control · Mathematics 2024-10-08 Felipe Lara , Nguyen Van Tuyen , Tran Van Nghi

In this note we study the existence of a solution to the survey-propagation equations for the random K-satisfiability problem for a given instance. We conjecture that when the number of variables goes to infinity, the solution of these…

Computational Complexity · Computer Science 2007-05-23 Giorgio Parisi

We develop two adaptive discretization algorithms for convex semi-infinite optimization, which terminate after finitely many iterations at approximate solutions of arbitrary precision. In particular, they terminate at a feasible point of…

Optimization and Control · Mathematics 2022-01-14 Jochen Schmid , Miltiadis Poursanidis

We study time-inconsistent recursive stochastic control problems, i.e., for which the Bellman principle of optimality does not hold. For this class of problems classical optimal controls may fail to exist, or to be relevant in practice, and…

Optimization and Control · Mathematics 2024-03-14 Elisa Mastrogiacomo , Marco Tarsia

Nash equilibria provide a principled framework for modeling interactions in multi-agent decision-making and control. However, many equilibrium-seeking methods implicitly assume that each agent has access to the other agents' objectives and…

Computer Science and Game Theory · Computer Science 2026-03-19 Mahdis Rabbani , Navid Mojahed , Shima Nazari

We establish fundamental limits on estimation accuracy for the noisy 20 questions problem with measurement-dependent noise and introduce optimal non-adaptive procedures that achieve these limits. The minimal achievable resolution is defined…

Information Theory · Computer Science 2021-01-12 Lin Zhou , Alfred Hero

Modifying the reward-biased maximum likelihood method originally proposed in the adaptive control literature, we propose novel learning algorithms to handle the explore-exploit trade-off in linear bandits problems as well as generalized…

Machine Learning · Computer Science 2020-10-09 Yu-Heng Hung , Ping-Chun Hsieh , Xi Liu , P. R. Kumar
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