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Questions in causality, control, and reinforcement learning go beyond the classical machine learning task of prediction under i.i.d. observations. Instead, these fields consider the problem of learning how to actively perturb a system to…

Poset-causal systems form a class of decentralized systems introduced by Shah and Parrilo [32] and studied mainly in the context of optimal decentralized control. In this paper we develop part of the realization theory for poset-causal…

Optimization and Control · Mathematics 2020-10-13 Sanne ter Horst , Jaccie Zeelie

Motivated by a recent conjecture concerning the expressiveness of declarative networking, we propose a formal computation model for "eventually consistent" distributed querying, based on relational transducers. A tight link has been…

Databases · Computer Science 2011-06-29 Tom Ameloot , Frank Neven , Jan Van den Bussche

Anomaly detection usually assumes that abnormality is an intrinsic property of an observation. A defect is a defect, and a rare object is rare, regardless of where it appears. Many real-world anomalies do not work this way. A runner on a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Shashank Mishra , Didier Stricker , Jason Rambach

Recent advancements in large language models have sparked interest in their extraordinary and near-superhuman capabilities, leading researchers to explore methods for evaluating and optimizing these abilities, which is called…

Computer Vision and Pattern Recognition · Computer Science 2024-02-07 Jianyuan Guo , Hanting Chen , Chengcheng Wang , Kai Han , Chang Xu , Yunhe Wang

We propose a new measure of relative incompatibility for a quantum system with respect to two non-commuting observables, and call it quantumness of relative incompatibility. In case of a classical state, order of observation is…

Quantum Physics · Physics 2019-09-30 Manish Kumar Shukla , Rounak Mundra , Arun K Pati , Indranil Chakrabarty , Junde Wu

This paper considers the problem of determining an optimal control action based on observed data. We formulate the problem assuming that the system can be modelled by a nonlinear state-space model, but where the model parameters, state and…

Optimization and Control · Mathematics 2021-07-02 Johannes N. Hendriks , James R. Z. Holdsworth , Adrian G. Wills , Thomas B. Schon , Brett Ninness

We consider a class of systems over finite alphabets with linear internal dynamics, finite-valued control inputs and finitely quantized outputs. We motivate the need for a new notion of observability and propose three new notions of output…

Optimization and Control · Mathematics 2016-07-13 Donglei Fan , Danielle C. Tarraf

We consider a supervisory control problem of a discrete event system (DES) under partial observation, where a control specification is given by a fragment of linear temporal logic. We design an on-line supervisor that dynamically computes…

Systems and Control · Electrical Eng. & Systems 2020-03-30 Ami Sakakibara , Toshimitsu Ushio

Self-supervision provides effective representations for downstream tasks without requiring labels. However, existing approaches lag behind fully supervised training and are often not thought beneficial beyond obviating or reducing the need…

Machine Learning · Computer Science 2019-10-30 Dan Hendrycks , Mantas Mazeika , Saurav Kadavath , Dawn Song

In the development of operational semantics of concurrent systems, a key decision concerns the adoption of a suitable notion of execution model, which basically amounts to choosing a class of partial orders according to which events are…

Formal Languages and Automata Theory · Computer Science 2024-07-19 Maciej Koutny , Lukasz Mikulski

Applications of Reinforcement Learning (RL), in which agents learn to make a sequence of decisions despite lacking complete information about the latent states of the controlled system, that is, they act under partial observability of the…

Machine Learning · Computer Science 2022-05-26 Qinghua Liu , Alan Chung , Csaba Szepesvári , Chi Jin

Relational Quantum Mechanics (RQM) treats quantum states as observer-dependent facts rather than absolute properties. While this relational stance is conceptually attractive, it raises concerns about empirical confirmation, particularly in…

History and Philosophy of Physics · Physics 2026-03-05 Bethany Terris

Our earlier work titled: "Win-move is Coordination-Free (Sometimes)" has shown that the classes of queries that can be distributedly computed in a coordination-free manner form a strict hierarchy depending on the assumptions of the model…

Databases · Computer Science 2015-03-20 Daniel Zinn

The problem of corrupted data, missing features, or missing modalities continues to plague the modern machine learning landscape. To address this issue, a class of regularization methods that enforce consistency between imputed and fully…

Machine Learning · Computer Science 2026-02-03 Yinsong Wang , Shahin Shahrampour

For arbitrary linear time-invariant systems, the existence of a strong functional observer is investigated. Such observer determines, from the available measurement on the plant, an estimate of a function of the state and the input. This…

Systems and Control · Electrical Eng. & Systems 2025-02-07 Michael Di Loreto , Damien Eberard

In this note, we will survey the existing convergence results for random variables under sublinear expectations, and prove some new results. Concretely, under the assumption that the sublinear expectation has the monotone continuity…

Probability · Mathematics 2017-04-28 Ze-Chun Hu , Qian-Qian Zhou

The most basic scenario of quantum control involves the organized manipulation of pure dynamical states of the system by means of unitary transformations. Recently, Vilela Mendes and Mank'o have shown that the conditions for controllability…

Quantum Physics · Physics 2009-11-10 A. Mandilara , J. W. Clark

Recently, we have proposed two complementary approaches, top-down and bottom-up, to multilevel supervisory control of discrete-event systems. In this paper, we compare and combine these approaches. The combined approach has strong features…

Optimization and Control · Mathematics 2016-08-07 Jan Komenda , Tomáš Masopust , Jan H. van Schuppen

We provide a new perspective to understand why reinforcement learning (RL) struggles with robustness and generalization. We show, by examples, that local optimal policies may contain unstable control for some dynamic parameters and…

Robotics · Computer Science 2023-11-03 Bing Song , Jean-Jacques Slotine , Quang-Cuong Pham