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Certification for machine learning is proving that no adversarial sample can evade a model within a range under certain conditions, a necessity for safety-critical domains. Common certification methods for segmentation use a flat set of…

Machine Learning · Computer Science 2024-06-05 Alaa Anani , Tobias Lorenz , Bernt Schiele , Mario Fritz

Hierarchical clustering is a stronger extension of one of today's most influential unsupervised learning methods: clustering. The goal of this method is to create a hierarchy of clusters, thus constructing cluster evolutionary history and…

Data Structures and Algorithms · Computer Science 2021-01-14 MohammadTaghi Hajiaghayi , Marina Knittel

Symmetry and dominance breaking can be crucial for solving hard combinatorial search and optimisation problems, but the correctness of these techniques sometimes relies on subtle arguments. For this reason, it is desirable to produce…

Artificial Intelligence · Computer Science 2023-08-17 Bart Bogaerts , Stephan Gocht , Ciaran McCreesh , Jakob Nordström

A physical limitation in quantum circuit design is the fact that gates in a quantum system can only act on qubits that are physically adjacent in the architecture. To overcome this problem, SWAP gates need to be inserted to make the circuit…

Optimization and Control · Mathematics 2025-08-28 Frank de Meijer , Dion Gijswijt , Renata Sotirov

This paper considers the problem of canonical-correlation analysis (CCA) (Hotelling, 1936) and, more broadly, the generalized eigenvector problem for a pair of symmetric matrices. These are two fundamental problems in data analysis and…

Machine Learning · Computer Science 2016-05-30 Rong Ge , Chi Jin , Sham M. Kakade , Praneeth Netrapalli , Aaron Sidford

The assumption of maximum parallelism support for the successful realization of scalable quantum computers has led to homogeneous, ``sea-of-qubits'' architectures. The resulting architectures overcome the primary challenges of reliability…

We present a fast algorithm for approximate Canonical Correlation Analysis (CCA). Given a pair of tall-and-thin matrices, the proposed algorithm first employs a randomized dimensionality reduction transform to reduce the size of the input…

Data Structures and Algorithms · Computer Science 2013-05-03 Haim Avron , Christos Boutsidis , Sivan Toledo , Anastasios Zouzias

Numerical optimization (solving optimization problems using digital computers) currently dominates but has three major drawbacks: high energy consumption, poor scalability, and lack of an execution time certificate. To address these…

Optimization and Control · Mathematics 2025-11-18 Liang Wu , Ambrose Adegbege , Yongduan Song , Richard D. Braatz

We present two types of meta-algorithm that can greatly improve the accuracy of existing algorithms for integrating the equations of motion of dynamical systems. The first meta-algorithm takes an integrator that is time-symmetric only for…

Astrophysics · Physics 2007-05-23 Piet Hut , Yoko Funato , Eiichiro Kokubo , Junichiro Makino , Steve McMillan

The capacity to custom tailor the properties of quantum matter and materials is a central requirement for enlarging their range of possible functionalities. A particularly promising route is the use of driving protocols to engineer specific…

Quantum Physics · Physics 2025-02-19 Zhanpeng Fu , Roderich Moessner , Hongzheng Zhao , Marin Bukov

Overcoming the influence of noise and imperfections in quantum devices is one of the main challenges for viable quantum applications. In this article, we present different protocols, which we denote as "superposed quantum error mitigation",…

Through numerical simulations we analyze the synchronization time and the Lyapunov dimension of a coupled map lattice consisting of a chain of chaotic logistic maps exhibiting power law interactions. From the observed behaviors we find a…

Chaotic Dynamics · Physics 2016-08-16 Sandro E. de Souza Pinto , José T. Lunardi , Abdala M. Saleh , Antonio M. Batista

We consider the stability of synchronized chaos in coupled map lattices and in coupled ordinary differential equations. Applying the theory of Hermitian and positive semidefinite matrices we prove two results that give simple bounds on…

Chaotic Dynamics · Physics 2009-11-07 Govindan Rangarajan , Mingzhou Ding

Synchronization of coupled continuous-time linear systems is studied in a general setting. For identical neutrally-stable linear systems that are detectable from their outputs, it is shown that a linear output feedback law exists under…

Optimization and Control · Mathematics 2008-01-22 S. Emre Tuna

We present benchmarks of the parity transformation for the Quantum Approximate Optimization Algorithm (QAOA). We analyse the gate resources required to implement a single QAOA cycle for real-world scenarios. In particular, we consider…

Quantum Physics · Physics 2023-03-20 Michael Fellner , Kilian Ender , Roeland ter Hoeven , Wolfgang Lechner

We develop a mathematical framework for quantum time transfer based on commuting families of Hamiltonians and synchronization observables. The synchronization subspace is defined as the kernel of a difference operator between local clocks,…

Quantum Physics · Physics 2025-10-09 Nicholas R. Allgood

We provide a complete geometric description of the set of synchronous quantum correlations for the three experiment two outcome scenario. We show that these correlations form a closed set. Moreover, every correlation in this set can be…

Quantum Physics · Physics 2020-05-04 Travis B. Russell

Synchronization in the networks of coupled oscillators is a widely studied topic in different areas. It is well-known that synchronization occurs if the connectivity of the network dominates heterogeneity of the oscillators. Despite…

Optimization and Control · Mathematics 2018-09-20 Elizabeth Y. Huang , Saber Jafarpour , Francesco Bullo

The asymptotic behavior of estimates and information criteria in linear models are studied in the context of hierarchically correlated sampling units. The work is motivated by biological data collected on species where autocorrelation is…

Applications · Statistics 2021-10-20 Cécile Ané

In this contribution we apply an adaptive model hierarchy, consisting of a full-order model, a reduced basis reduced order model, and a machine learning surrogate, to parametrized linear-quadratic optimal control problems. The involved…

Optimization and Control · Mathematics 2024-02-19 Hendrik Kleikamp
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