11 papers
Wrench-Based Bayesian Pose Estimation via Matrix--Fisher Gaussian Inference
Jianyu Chen, Lin Yang, Yibang Li +2
In this paper, a residual-safeguarded local Matrix Fisher--Gaussian (MFG) inference method is developed for wrench-based pose estimation on . The…
Universality of kernels on Riemannian symmetric spaces
Salem Said, Nathaël Da Costa, Franziskus Steinert +1
We investigate universality properties of continuous, positive-definite invariant kernels on Riemannian symmetric spaces, providing a unified harmonic-analytic characterization acr…
Horospherical Depth and Busemann Median on Hadamard Manifolds
Yangdi Jiang, Xiaotian Chang, Cyrus Mostajeran
\We introduce the horospherical depth, an intrinsic notion of statistical depth on Hadamard manifolds, and define the Busemann median as the set of its maximizers. The construction…
Intrinsic Muon: Spectral Optimization on Riemannian Matrix Manifolds
Yibang Li, Bihari Lal Pandey, Ravi Sah +4
Muon and related norm-constrained matrix optimizers have become central to large-scale learning problems. They are formulated as a linear maximization oracle (LMO) over an ambient…
Robust Least-Squares Optimization for Data-Driven Predictive Control: A Geometric Approach
Shreyas Bharadwaj, Bamdev Mishra, Cyrus Mostajeran +3
The paper studies a geometrically robust least-squares problem that extends classical and norm-based robust formulations. Rather than minimizing residual error for fixed or perturb…
Geometric Renyi Differential Privacy: Ricci Curvature Characterized by Heat Diffusion Mechanisms
Xiaotian Chang, Yangdi Jiang, Cyrus Mostajeran +1
In this paper, we develop a novel privacy mechanism for Riemannian manifold-valued data. Our key contribution lies in uncovering unexpected connections among geometric analysis, he…