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Robust Optimal Control (ROC) with adjustable uncertainties has proven to be effective in addressing critical challenges within modern energy networks, especially the reserve and provision problem. However, prior research on ROC with…

Systems and Control · Electrical Eng. & Systems 2023-12-19 Yun Li , Neil Yorke-Smith , Tamas Keviczky

The paper investigates stochastic resource allocation problems with scarce, reusable resources and non-preemtive, time-dependent, interconnected tasks. This approach is a natural generalization of several standard resource management…

Machine Learning · Computer Science 2014-01-16 Balázs Csanád Csáji , László Monostori

Reliability is a serious concern for future extreme-scale high-performance computing (HPC) systems. While the HPC community has developed various resilience solutions, the solution space remains fragmented. There are no formal methods and…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-01 Saurabh Hukerikar , Christian Engelmann

Regression test case prioritization (RTCP) aims to improve the rate of fault detection by executing more important test cases as early as possible. Various RTCP techniques have been proposed based on different coverage criteria. Among them,…

Software Engineering · Computer Science 2020-07-02 Rubing Huang , Quanjun Zhang , Dave Towey , Weifeng Sun , Jinfu Chen

There has been a considerable amount of interest in recent years in the problem of workflow satisfiability, which asks whether the existence of constraints in a workflow specification makes it impossible to allocate authorized users to each…

Data Structures and Algorithms · Computer Science 2019-04-17 Jason Crampton , Gregory Gutin , Diptapriyo Majumdar

Equipping approximate dynamic programming (ADP) with inputconstraints has a tremendous significance. This enables ADP to be applied tothe systems with actuator limitations, which is quite common for dynamicalsystems. In a conventional…

Optimization and Control · Mathematics 2018-05-24 Xuefeng Bao , Zhi-Hong Mao , Nitin Sharma

Healthcare data often come from multiple sites in which the correlations between confounding variables can vary widely. If deep learning models exploit these unstable correlations, they might fail catastrophically in unseen sites. Although…

Machine Learning · Computer Science 2023-10-25 Minh Nguyen , Alan Q. Wang , Heejong Kim , Mert R. Sabuncu

In this paper, we investigate the control of a cyber-physical system (CPS) while accounting for its vulnerability to external attacks. We formulate a constrained stochastic problem with a robust constraint to ensure robust operation against…

Optimization and Control · Mathematics 2024-07-18 Nishanth Venkatesh , Aditya Dave , Ioannis Faros , Andreas A. Malikopoulos

Understanding the application resilience in the presence of faults is critical to address the HPC resilience challenge. Currently, we largely rely on random fault injection (RFI) to quantify the application resilience. However, RFI provides…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-05-02 Luanzheng Guo , Hanlin He , Dong Li

In an open information systems paradigm, real-time context-awareness is vital for the success of cooperation, therefore dynamic security attributes of partners should considered in coalition for avoiding security conflicts. Furthermore, the…

Cryptography and Security · Computer Science 2013-05-09 Ziyi Su , Frederique Biennier

Access control is a security mechanism designed to ensure that only authorized users can access specific resources. Cross-domain access control involves access to resources across different organizations, institutions, or applications.…

Cryptography and Security · Computer Science 2025-12-01 Aiyao Zhang , Xiaodong Lee , Zhixian Zhuang , Jiuqi Wei , Yufan Fu , Botao Peng

In this paper, we present Robust Model Predictive Control (MPC) problems with adjustable uncertainty sets. In contrast to standard Robust MPC problems with known uncertainty sets, we treat the uncertainty sets in our problems as additional…

Optimization and Control · Mathematics 2018-09-21 Yeojun Kim , Xiaojing Zhang , Jacopo Guanetti , Francesco Borrelli

We investigate the important problem of certifying stability of reinforcement learning policies when interconnected with nonlinear dynamical systems. We show that by regulating the input-output gradients of policies, strong guarantees of…

Systems and Control · Computer Science 2018-10-30 Ming Jin , Javad Lavaei

In this paper, we propose a data-driven approach to formally verify the safety of (potentially) unknown discrete-time continuous-space stochastic systems. The proposed framework is based on a notion of barrier certificates together with…

Systems and Control · Electrical Eng. & Systems 2021-12-24 Ali Salamati , Abolfazl Lavaei , Sadegh Soudjani , Majid Zamani

Reinforcement learning (RL) for reachability specifications is fundamental in sequential decision-making, yet theoretical guarantees remain less explored. A recent work achieves asymptotic convergence to optimal policies. However, this…

Machine Learning · Computer Science 2026-05-26 Amogh Palasamudram , Jakub Svoboda , Suguman Bansal , Krishnendu Chatterjee

Proving the NP-completeness of pencil-and-paper puzzles typically relies on reductions from combinatorial problems such as the satisfiability problem (SAT). Although the properties of these problems are well studied, their purely…

Computational Complexity · Computer Science 2026-03-10 Kosuke Susukita , Junichi Teruyama

Decidability of the problems of unboundedness and simultaneous unboundedness (aka. the diagonal problem) for higher-order recursion schemes was established by Clemente, Parys, Salvati, and Walukiewicz (2016). Then a procedure of optimal…

Logic in Computer Science · Computer Science 2022-04-26 David Barozzini , Paweł Parys , Jan Wróblewski

Electoral control refers to attempts by an election's organizer ("the chair") to influence the outcome by adding/deleting/partitioning voters or candidates. The groundbreaking work of Bartholdi, Tovey, and Trick [BTT92] on (constructive)…

Computer Science and Game Theory · Computer Science 2008-09-26 Edith Hemaspaandra , Lane A. Hemaspaandra , Joerg Rothe

We introduce some classical complexity-theoretic techniques to Parameterized Complexity. First, we study relativization for the machine models that were used by Chen, Flum, and Grohe (2005) to characterize a number of parameterized…

Computational Complexity · Computer Science 2018-07-18 Ralph Christian Bottesch

We study a sequential decision-making problem motivated by recent regulatory and technological shifts that limit access to individual user data in recommender systems (RSs), leaving only population-level preference information. This…

Artificial Intelligence · Computer Science 2025-07-08 Gur Keinan , Omer Ben-Porat