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Learning Intra-class Multimodal Distributions with Orthonormal Matrices

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First Order Methods for Optimization on Riemannian Manifolds

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An Online Riemannian PCA for Stochastic Canonical Correlation Analysis

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Stochastic Variance Reduced Riemannian EigensolverPreprint

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Hyperbolic Deep Learning for Chinese Natural Language UnderstandingPreprint

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Convergence Analysis of Riemannian Stochastic Approximation SchemesPreprint

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Variance reduction for Riemannian non-convex optimization with batch size adaptationPreprint

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Spherical Sliced-WassersteinPreprint

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Learning a Better SPD Network for Signal Classification: A Riemannian Batch Normalization Method

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Metric-Driven Voronoi Diagrams: A Comprehensive Mathematical Framework

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Efficient Random Walks on Riemannian Manifolds

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Logical Relation Modeling and Mining in Hyperbolic Space for Recommendation

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Adversarial Attacks on Hyperbolic Networks

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Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding

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Distributed Riemannian stochastic gradient tracking algorithm on the Stiefel manifold

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A Diffusion-Map-Based Algorithm for Gradient Computation on Manifolds and Applications

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Accelerated algorithms for convex and non-convex optimization on manifolds

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A hyperbolic approach for learning communities on graphs

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Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold

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Faster Riemannian Newton-type optimization by subsampling and cubic regularization

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Analog Product Coding for Over-the-Air Aggregation Over Burst-Sparse Interference Multiple-Access Channels

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Riemannian Diffusion Adaptation over Graphs with Application to Online Distributed PCA

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Hyperbolic Graph Wavelet Neural Network

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The Ultimate Upper Bound on the Injectivity Radius of the Stiefel Manifold

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Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs

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Learning a Gradient-free Riemannian Optimizer on Tangent Spaces

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Linear convergence of the subspace constrained mean shift algorithm: from Euclidean to directional data

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Spherical coordinates from persistent cohomology

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A Riemannian gossip approach to decentralized matrix completionPreprint

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Relative Natural Gradient for Learning Large Complex ModelsPreprint

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Stochastic Primal-Dual Method on Riemannian Manifolds with Bounded Sectional CurvaturePreprint

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Quantitative Rates and Fundamental Obstructions to Non-Euclidean Universal Approximation with Deep Narrow Feed-Forward Networks.Preprint

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On Riemannian Stochastic Approximation Schemes with Fixed Step-SizePreprint

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DESYR: Definition and Syntactic Representation Based Claim Detection on the WebPreprint

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FisheyeHDK: Hyperbolic Deformable Kernel Learning for Ultra-Wide Field-of-View Image Recognition

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Tree-Like Interaction Learning for Bundle Recommendation

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Stochastic first-order learning for large-scale flexibly tied Gaussian mixture models

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Differentially private Riemannian optimization

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Comparing Hyperbolic Graph Embedding models on Anomaly Detection for Cybersecurity

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Geometric Machine Learning

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On Target Representation in Continuous-output Neural Machine Translation

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Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method for Submanifold Optimization

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Adaptive Trust-Region Method on Riemannian Manifold

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Structured Regularization for SPD Optimization with Side Information

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Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation

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Textual Evidence Mining via Spherical Heterogeneous Information Network Embedding

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Fine-grained Optimization of Deep Neural NetworksPreprint

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A Brief Introduction to Manifold OptimizationPreprint

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An Ode to an ODEPreprint

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Escape saddle points faster on manifolds via perturbed Riemannian stochastic recursive gradientPreprint

Han, A., & Gao, J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.12191 · Cited by 2

Nonparametric multimodal regression for circular dataPreprint

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Switch Spaces: Learning Product Spaces with Sparse GatingPreprint

Zhang, S., Tay, Y., Jiang, W., Juan, D.-C., & Zhang, C. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.08688 · Cited by 2

Unit Ball Model for Embedding Hierarchical Structures in the Complex Hyperbolic SpacePreprint

Xiao, H., Jiang, C., Song, Y., Zhang, J., & Xiong, J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.03966 · Cited by 2

Hyperspherical Dirac Mixture ReapproximationPreprint

Li, K., Pfaff, F., & Hanebeck, U. D. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.10411 · Cited by 2

Pareto Navigation Gradient Descent: a First-Order Algorithm for Optimization in Pareto SetPreprint

Ye, M., & Liu, Q. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.08713 · Cited by 2

Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech ProcessingPreprint

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Dual stochastic natural gradient descent

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Dimensionality and Curvature Selection of Graph Embedding using Decomposed Normalized Maximum Likelihood Code-Length

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GrassCaré: Visualizing the Grassmannian on the Poincaré Disk

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Convergence of variational Monte Carlo simulation and scale-invariant pre-training

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Task-Driven Wavelets Using Constrained Empirical Risk Minimization

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A Comprehensive Method for Example-Based Color Transfer with Holistic–Local Balancing and Unit-Wise Riemannian Information Gradient Acceleration

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Data-reuse recursive least-squares algorithm with Riemannian manifold constraint

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VoRec: Enhancing Recommendation with Voronoi Diagram in Hyperbolic Space

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Hyperbolic Multi-Criteria Rating Recommendation

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Hyperbolic graph representation learning: methods, applications and challenges—A survey

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Interactive Graph Learning for Multilevel Network Alignment

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Zeroth-Order Distributed Stochastic Optimization Over Riemannian Manifolds

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A generalized k–Lα centroids algorithm for DT-MRI segmentation

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Curvature-guided geometric gating graph collaborative filtering with topology-aware augmentation

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HYPDAE: Hyperbolic Diffusion Autoencoders for Hierarchical Few-Shot Image Generation

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Adaptive Riemannian optimization for multi-scale diffeomorphic matching

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A Trust Optimization Region of the Quantum Natural Gradient for the Large Damping Domain

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Random Pairwise Gossip on $\text{CAT}(\kappa)$ Metric Spaces

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Riemannian stochastic variance reduced gradient on Grassmann manifoldPreprint

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Riemannian Stochastic Variance Reduced Gradient Algorithm with Retraction and Vector Transport

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Riemannian adaptive stochastic gradient algorithms on matrix manifoldsPreprint

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