Manopt, a Matlab toolbox for optimization on manifolds

23 August 2013

Papers citing "Manopt, a Matlab toolbox for optimization on manifolds"

50 / 237 papers shown

Title
Riemannian stochastic recursive momentum method for non-convex optimization Andi Han Junbin Gao ODL 28 17 0 11 Aug 2020
Intrinsic Gaussian Processes on Manifolds and Their Accelerations by Symmetry Ke Ye Mu Niu P. Cheung Zhenwen Dai Yuan Liu 6 2 0 25 Jun 2020
Automatic Estimation of Self-Reported Pain by Interpretable Representations of Motion Dynamics Benjamin Szczapa Mohamed Daoudi Stefano Berretti P. Pala A. Bimbo Z. Hammal 16 11 0 24 Jun 2020
A Deep Learning Framework for Hybrid Beamforming Without Instantaneous CSI Feedback Ahmet M. Elbir 14 31 0 19 Jun 2020
Natural evolution strategies and variational Monte Carlo Tianchen Zhao Giuseppe Carleo J. Stokes S. Veerapaneni 11 5 0 09 May 2020
Geoopt: Riemannian Optimization in PyTorch Max Kochurov R. Karimov Sergei Kozlukov 22 114 0 06 May 2020
Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold Bokun Wang Shiqian Ma Lingzhou Xue 29 18 0 03 May 2020
Geomstats: A Python Package for Riemannian Geometry in Machine Learning Nina Miolane Alice Le Brigant Johan Mathe Benjamin Hou N. Guigui ... Christian Shewmake Bernhard Kainz Claire Donnat S. Holmes Xavier Pennec AI4CE 31 21 0 07 Apr 2020
Geometry-aware Domain Adaptation for Unsupervised Alignment of Word Embeddings Pratik Jawanpuria Mayank Meghwanshi Bamdev Mishra 17 20 0 06 Apr 2020
Learning with Semi-Definite Programming: new statistical bounds based on fixed point analysis and excess risk curvature Stéphane Chrétien Mihai Cucuringu Guillaume Lecué Lucie Neirac 11 5 0 04 Apr 2020
Certifiable Relative Pose Estimation Mercedes Garcia-Salguero Jesus Briales Javier González Jiménez 27 27 0 30 Mar 2020
A Family of Deep Learning Architectures for Channel Estimation and Hybrid Beamforming in Multi-Carrier mm-Wave Massive MIMO Ahmet M. Elbir Kumar Vijay Mishra Bhavani Shankar Björn E. Ottersten 11 38 0 20 Dec 2019
A Probabilistic approach for Learning Embeddings without Supervision U. Dutta Mehrtash Harandi C. Sekhar SSL 43 0 0 17 Dec 2019
MM Algorithms for Distance Covariance based Sufficient Dimension Reduction and Sufficient Variable Selection Runxiong Wu Xin Chen 11 8 0 13 Dec 2019
Robust Feature-Based Point Registration Using Directional Mixture Model Saman Fahandezh-Saadi Di Wang Masayoshi Tomizuka 3DPC 11 0 0 25 Nov 2019
Distributed Certifiably Correct Pose-Graph Optimization Yulun Tian Kasra Khosoussi David M. Rosen Jonathan P. How 48 69 0 09 Nov 2019
Convex Optimisation for Inverse Kinematics Tarun Yenamandra Florian Bernard Jiayi Wang Franziska Mueller Christian Theobalt 19 9 0 24 Oct 2019
Projection-free nonconvex stochastic optimization on Riemannian manifolds Melanie Weber S. Sra 29 17 0 09 Oct 2019
Self-Paced Multi-Label Learning with Diversity Seyed Amjad Seyedi Siamak Ghodsi F. Akhlaghian Mahdi Jalili P. Moradi 16 5 0 08 Oct 2019
A theorem of Kalman and minimal state-space realization of Vector Autoregressive Models Du Nguyen 11 0 0 06 Oct 2019
Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion Chieh-Tsai Wu Jared Miller Yale Chang Octavia Camps Jennifer Dy 20 1 0 06 Sep 2019
Solving Interpretable Kernel Dimension Reduction Chieh-Tsai Wu Jared Miller Yale Chang Octavia Camps Jennifer Dy 17 7 0 06 Sep 2019
Discriminative Video Representation Learning Using Support Vector Classifiers Jue Wang A. Cherian 25 5 0 05 Sep 2019
Algebraic Representations for Volumetric Frame Fields David R Palmer D. Bommes Justin Solomon 11 40 0 15 Aug 2019
A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics Anirudha Majumdar G. Hall Amir Ali Ahmadi 27 102 0 14 Aug 2019
Variational Bayes on Manifolds Minh-Ngoc Tran D. Nguyen Duy Nguyen 22 23 0 08 Aug 2019
Fitting, Comparison, and Alignment of Trajectories on Positive Semi-Definite Matrices with Application to Action Recognition Benjamin Szczapa Mohamed Daoudi Stefano Berretti A. Bimbo P. Pala E. Massart 24 11 0 01 Aug 2019
Canonical Correlation Analysis (CCA) Based Multi-View Learning: An Overview Chenfeng Guo Dongrui Wu HAI 11 29 0 03 Jul 2019
Riemannian optimization on the simplex of positive definite matrices Bamdev Mishra Hiroyuki Kasai Pratik Jawanpuria 10 3 0 25 Jun 2019
Escaping from saddle points on Riemannian manifolds Yue Sun Nicolas Flammarion Maryam Fazel 31 71 0 18 Jun 2019
Manifold-regression to predict from MEG/EEG brain signals without source modeling D. Sabbagh Pierre Ablin Gaël Varoquaux Alexandre Gramfort D. Engemann 14 58 0 04 Jun 2019
Multi-reference factor analysis: low-rank covariance estimation under unknown translations Boris Landa Y. Shkolnisky 15 3 0 01 Jun 2019
Joint Representation of Multiple Geometric Priors via a Shape Decomposition Model for Single Monocular 3D Pose Estimation Mengxi Jiang Zhuliang Yu Cuihua Li Yunqi Lei 29 0 0 31 May 2019
Free Component Analysis: Theory, Algorithms & Applications Hao Wu R. Nadakuditi CML 9 2 0 05 May 2019
Multi-modal 3D Shape Reconstruction Under Calibration Uncertainty using Parametric Level Set Methods Moshe Eliasof Andrei Sharf Eran Treister 3DV 20 5 0 23 Apr 2019
Probabilistic Permutation Synchronization using the Riemannian Structure of the Birkhoff Polytope Tolga Birdal Umut Simsekli 35 37 0 11 Apr 2019
Analyzing Dynamical Brain Functional Connectivity As Trajectories on Space of Covariance Matrices Mengyu Dai Zhengwu Zhang Anuj Srivastava 15 31 0 10 Apr 2019
Sliced Wasserstein Generative Models Jiqing Wu Zhiwu Huang Dinesh Acharya Wen Li Janine Thoma D. Paudel Luc Van Gool DiffM 30 125 0 10 Apr 2019
Low-rank approximations of hyperbolic embeddings Pratik Jawanpuria Mayank Meghwanshi Bamdev Mishra BDL 22 11 0 18 Mar 2019
Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold Hiroyuki Kasai Bamdev Mishra 11 1 0 11 Feb 2019
Manifold Optimization Assisted Gaussian Variational Approximation Bingxin Zhou Junbin Gao Minh-Ngoc Tran Richard Gerlach 21 6 0 11 Feb 2019
Random Matrix Improved Covariance Estimation for a Large Class of Metrics Malik Tiomoko Florent Bouchard G. Ginolhac Romain Couillet 13 13 0 07 Feb 2019
Riemannian optimization with a preconditioning scheme on the generalized Stiefel manifold B. Shustin H. Avron 6 9 0 05 Feb 2019
Riemannian adaptive stochastic gradient algorithms on matrix manifolds Hiroyuki Kasai Pratik Jawanpuria Bamdev Mishra 28 3 0 04 Feb 2019
Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold Shixiang Chen Shiqian Ma Anthony Man-Cho So Tong Zhang 31 15 0 02 Nov 2018
Heterogeneous multireference alignment for images with application to 2-D classification in single particle reconstruction Chao Ma Tamir Bendory Nicolas Boumal F. Sigworth A. Singer 27 26 0 12 Oct 2018
McTorch, a manifold optimization library for deep learning Mayank Meghwanshi Pratik Jawanpuria Anoop Kunchukuttan Hiroyuki Kasai Bamdev Mishra AI4CE 28 41 0 03 Oct 2018
Learning Paths from Signature Tensors Max Pfeffer A. Seigal Bernd Sturmfels 14 26 0 05 Sep 2018
Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach Pratik Jawanpuria Arjun Balgovind Anoop Kunchukuttan Bamdev Mishra 38 77 0 27 Aug 2018
Grassmannian Learning: Embedding Geometry Awareness in Shallow and Deep Learning Jiayao Zhang Guangxu Zhu R. Heath Kaibin Huang 20 41 0 07 Aug 2018