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Gaussian process (GP) based Bayesian optimization (BO) is a powerful method for optimizing black-box functions efficiently. The practical performance and theoretical guarantees of this approach depend on having the correct GP hyperparameter…

Machine Learning · Statistics 2024-06-07 Huong Ha , Vu Nguyen , Hung Tran-The , Hongyu Zhang , Xiuzhen Zhang , Anton van den Hengel

In this paper, we develop a new technique to obtain nearly optimal estimates of the computational resolution limits introduced in Appl. Comput. Harmon. Anal. 56 (2022) 402-446; IEEE Trans. Inf. Theory 67(7) (2021) 4812-4827; Inverse Probl.…

Image and Video Processing · Electrical Eng. & Systems 2022-05-17 Ping Liu , Habib Ammari

This paper presents a simple algebraic method to estimate the pose of a camera relative to a planar target from $n \geq 4$ reference points with known coordinates in the target frame and their corresponding bearing measurements in the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Tarek Bouazza , Tarek Hamel , Claude Samson

Optical computing holds promise for high-speed, energy-efficient information processing, with diffractive optical networks emerging as a flexible platform for implementing task-specific transformations. A challenge, however, is the…

Machine Learning · Computer Science 2026-01-05 Yuhang Li , Shiqi Chen , Tingyu Gong , Aydogan Ozcan

Linear optical quantum circuits with photon number resolving (PNR) detectors are used for both Gaussian Boson Sampling (GBS) and for the preparation of non-Gaussian states such as Gottesman-Kitaev-Preskill (GKP), cat and NOON states. They…

Quantum Physics · Physics 2023-08-30 Robbe De Prins , Yuan Yao , Anuj Apte , Filippo M. Miatto

Preferential Bayesian optimisation (PBO) deals with optimisation problems where the objective function can only be accessed via preference judgments, such as "this is better than that" between two candidate solutions (like in A/B tests or…

Machine Learning · Computer Science 2021-04-02 Alessio Benavoli , Dario Azzimonti , Dario Piga

We consider optimization problems on Riemannian manifolds with equality and inequality constraints, which we call Riemannian nonlinear optimization (RNLO) problems. Although they have numerous applications, the existing studies on them are…

Optimization and Control · Mathematics 2021-06-16 Mitsuaki Obara , Takayuki Okuno , Akiko Takeda

Estimating the relative camera pose from $n \geq 5$ correspondences between two calibrated views is a fundamental task in computer vision. This process typically involves two stages: 1) estimating the essential matrix between the views, and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Javier Tirado-Garín , Javier Civera

Traditional projection-based reduced-order modeling approximates the full-order model by projecting it onto a linear subspace. With a fast-decaying Kolmogorov $n$-width of the solution manifold, the resulting reduced-order model (ROM) can…

Numerical Analysis · Mathematics 2026-03-27 Lijie Ji , Sabrina Rashid , Yanlai Chen , Zhu Wang

Ptychography is a powerful imaging technique that is used in a variety of fields, including materials science, biology, and nanotechnology. However, the accuracy of the reconstructed ptychography image is highly dependent on the accuracy of…

Applied Physics · Physics 2024-06-03 Ming Du , Tao Zhou , Junjing Deng , Daniel J. Ching , Steven Henke , Mathew J. Cherukara

The ODE method has been a workhorse for algorithm design and analysis since the introduction of the stochastic approximation. It is now understood that convergence theory amounts to establishing robustness of Euler approximations for ODEs,…

Optimization and Control · Mathematics 2020-10-02 Shuhang Chen , Adithya Devraj , Andrey Bernstein , Sean Meyn

The motion of planar ground vehicles is often non-holonomic, and as a result may be modelled by the 2 DoF Ackermann steering model. We analyse the feasibility of estimating such motion with a downward facing camera that exerts…

Robotics · Computer Science 2022-03-02 Ling Gao , Junyan Su , Jiadi Cui , Xiangchen Zeng , Xin Peng , Laurent Kneip

The algorithm for finding the optimal consistent approximation of an inconsistent pairwise comparisons matrix is based on a logarithmic transformation of a pairwise comparisons matrix into a vector space with the Euclidean metric.…

Other Computer Science · Computer Science 2015-05-11 W. W. Koczkodaj , M. Orlowski

Many combinatorial optimization problems can be formulated as the search for a subgraph that satisfies certain properties and minimizes the total weight. We assume here that the vertices correspond to points in a metric space and can take…

Data Structures and Algorithms · Computer Science 2024-12-25 Marin Bougeret , Jérémy Omer , Michael Poss

In recent years, there has been a growing interest in mathematical models leading to the minimization, in a symmetric matrix space, of a Bregman divergence coupled with a regularization term. We address problems of this type within a…

Optimization and Control · Mathematics 2022-06-10 A. Benfenati , E. Chouzenoux , J. -C. Pesquet

Graph-based multi-view spectral clustering methods have achieved notable progress recently, yet they often fall short in either oversimplifying pairwise relationships or struggling with inefficient spectral decompositions in…

Machine Learning · Computer Science 2025-11-14 Murong Yang , Shihui Ying , Xin-Jian Xu , Yue Gao

This paper addresses the problem of estimating the relative pose (position and orientation) and velocity of a vehicle with respect to a moving target, where both are equipped with Inertial Measurement Units (IMUs), assuming the availability…

Systems and Control · Electrical Eng. & Systems 2026-05-14 Alessandro Melis , Tarek Bouazza , Soulaimane Berkane , Tarek Hamel

Vehicle overtaking is one of the most complex driving maneuvers for autonomous vehicles. To achieve optimal autonomous overtaking, driving systems rely on multiple sensors that enable safe trajectory optimization and overtaking efficiency.…

Robotics · Computer Science 2026-03-31 Matej Rene Cihlar , Luka Šiktar , Branimir Ćaran , Marko Švaco

This paper presents a novel approach for predicting human poses using IMU data, diverging from previous studies such as DIP-IMU, IMUPoser, and TransPose, which use up to 6 IMUs in conjunction with bidirectional RNNs. We introduce two main…

Machine Learning · Computer Science 2024-02-20 Varun Ramani , Hossein Khayami , Yang Bai , Nakul Garg , Nirupam Roy

We address the problem of verifying neural networks against geometric transformations of the input image, including rotation, scaling, shearing, and translation. The proposed method computes provably sound piecewise linear constraints for…

Machine Learning · Computer Science 2024-09-24 Ben Batten , Yang Zheng , Alessandro De Palma , Panagiotis Kouvaros , Alessio Lomuscio