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Trivializations for Gradient-Based Optimization on Manifolds
v1v2 (latest)

Trivializations for Gradient-Based Optimization on Manifolds

Neural Information Processing Systems (NeurIPS), 2019
20 September 2019
Mario Lezcano Casado
ArXiv (abs)PDFHTML

Papers citing "Trivializations for Gradient-Based Optimization on Manifolds"

50 / 80 papers shown
PEOAT: Personalization-Guided Evolutionary Question Assembly for One-Shot Adaptive Testing
PEOAT: Personalization-Guided Evolutionary Question Assembly for One-Shot Adaptive Testing
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Ziwei Huang
Shangshang Yang
Ziwen Wang
Haiping Ma
Xingyi Zhang
125
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29 Nov 2025
Randomized HyperSteiner: A Stochastic Delaunay Triangulation Heuristic for the Hyperbolic Steiner Minimal Tree
Randomized HyperSteiner: A Stochastic Delaunay Triangulation Heuristic for the Hyperbolic Steiner Minimal Tree
Aniss Aiman Medbouhi
Alejandro García-Castellanos
Giovanni Luca Marchetti
Daniël M. Pelt
Erik J. Bekkers
Danica Kragic
LLMSV
145
0
0
10 Oct 2025
humancompatible.train: Implementing Optimization Algorithms for Stochastically-Constrained Stochastic Optimization Problems
humancompatible.train: Implementing Optimization Algorithms for Stochastically-Constrained Stochastic Optimization Problems
Andrii Kliachkin
Jana Lepšová
Gilles Bareilles
Jakub Marecek
108
0
0
25 Sep 2025
Neuro-Spectral Architectures for Causal Physics-Informed Networks
Neuro-Spectral Architectures for Causal Physics-Informed Networks
Arthur Bizzi
Leonardo M. Moreira
Márcio Marques
Leonardo Mendonça
Christian Júnior de Oliveira
...
Daniel Yukimura
Pavel Petrov
João M. Pereira
Tiago Novello
Lucas Nissenbaum
PINN
402
2
0
05 Sep 2025
rETF-semiSL: Semi-Supervised Learning for Neural Collapse in Temporal Data
rETF-semiSL: Semi-Supervised Learning for Neural Collapse in Temporal Data
Yuhan Xie
William Cappelletti
Mahsa Shoaran
Pascal Frossard
AI4TS
152
0
0
13 Aug 2025
Bridging Expressivity and Scalability with Adaptive Unitary SSMs
Bridging Expressivity and Scalability with Adaptive Unitary SSMs
Arjun Karuvally
Franz Nowak
Anderson T. Keller
Carmen Amo Alonso
T. Sejnowski
H. Siegelmann
199
2
0
07 Jul 2025
Load Balancing Mixture of Experts with Similarity Preserving Routers
Load Balancing Mixture of Experts with Similarity Preserving Routers
Nabil Omi
S. Sen
Ali Farhadi
MoE
387
13
0
16 Jun 2025
Efficient Robust Conformal Prediction via Lipschitz-Bounded Networks
Efficient Robust Conformal Prediction via Lipschitz-Bounded Networks
Thomas Massena
Léo Andéol
Thibaut Boissin
Franck Mamalet
Corentin Friedrich
M. Serrurier
Sébastien Gerchinovitz
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369
5
0
05 Jun 2025
Equivariant Eikonal Neural Networks: Grid-Free, Scalable Travel-Time Prediction on Homogeneous Spaces
Equivariant Eikonal Neural Networks: Grid-Free, Scalable Travel-Time Prediction on Homogeneous Spaces
Alejandro García-Castellanos
David R. Wessels
Nicky van den Berg
R. Duits
Daniël M. Pelt
Erik J. Bekkers
304
1
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21 May 2025
SPD Matrix Learning for Neuroimaging Analysis: Perspectives, Methods, and Challenges
SPD Matrix Learning for Neuroimaging Analysis: Perspectives, Methods, and Challenges
Ce Ju
Reinmar J. Kobler
Antoine Collas
M. Kawanabe
Cuntai Guan
Bertrand Thirion
444
0
0
26 Apr 2025
Hyperbolic Binary Neural Network
Hyperbolic Binary Neural NetworkIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024
Jun Chen
Jingyang Xiang
Tianxin Huang
Xiangrui Zhao
Yong Liu
MQ
258
1
0
08 Jan 2025
Guiding Neural Collapse: Optimising Towards the Nearest Simplex
  Equiangular Tight Frame
Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight FrameNeural Information Processing Systems (NeurIPS), 2024
Evan Markou
Thalaiyasingam Ajanthan
Stephen Gould
361
7
0
02 Nov 2024
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time SeriesInternational Conference on Learning Representations (ICLR), 2024
Byoungwoo Park
Hyungi Lee
Juho Lee
AI4TS
535
5
0
08 Oct 2024
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie GroupsInternational Conference on Learning Representations (ICLR), 2024
Zakhar Shumaylov
Peter Zaika
James Rowbottom
Ferdia Sherry
Melanie Weber
Carola-Bibiane Schönlieb
395
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0
03 Oct 2024
Robust Multi-view Co-expression Network Inference
Robust Multi-view Co-expression Network InferenceCLEaR (CLEaR), 2024
T. Pandeva
Martijs Jonker
Leendert Hamoen
Joris Mooij
Patrick Forré
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30 Sep 2024
Fast and Stable Riemannian Metrics on SPD Manifolds via Cholesky Product Geometry
Fast and Stable Riemannian Metrics on SPD Manifolds via Cholesky Product Geometry
Ziheng Chen
Yue Song
Xiao-Jun Wu
Andrii Zadaianchuk
267
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02 Jul 2024
Noisy Data Visualization using Functional Data Analysis
Noisy Data Visualization using Functional Data Analysis
Haozhe Chen
A. F. D. Correa
Guy Wolf
Kevin R. Moon
222
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05 Jun 2024
Riemannian coordinate descent algorithms on matrix manifolds
Riemannian coordinate descent algorithms on matrix manifolds
Andi Han
Pratik Jawanpuria
Bamdev Mishra
371
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04 Jun 2024
Learning Hamiltonian neural Koopman operator and simultaneously
  sustaining and discovering conservation law
Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation law
Jingdong Zhang
Qunxi Zhu
Wei Lin
318
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0
04 Jun 2024
Neural Controlled Differential Equations with Quantum Hidden Evolutions
Neural Controlled Differential Equations with Quantum Hidden Evolutions
Lingyi Yang
Zhen Shao
322
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30 Apr 2024
Deep Hashing via Householder Quantization
Deep Hashing via Householder Quantization
L. R. Schwengber
Lucas Resende
Paulo Orenstein
Roberto Imbuzeiro Oliveira
MQ
366
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0
07 Nov 2023
Manifold-Preserving Transformers are Effective for Short-Long Range
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Manifold-Preserving Transformers are Effective for Short-Long Range EncodingConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Ayan Sengupta
Md. Shad Akhtar
Tanmoy Chakraborty
240
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Exact and general decoupled solutions of the LMC Multitask Gaussian Process model
Exact and general decoupled solutions of the LMC Multitask Gaussian Process model
Olivier Truffinet
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J. Argaud
B. Bouriquet
293
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A survey of manifold learning and its applications for multimedia
A survey of manifold learning and its applications for multimediaInternational Journal of Signal Processing Systems (IJSPS), 2023
Hannes Fassold
225
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08 Sep 2023
Get the Best of Both Worlds: Improving Accuracy and Transferability by
  Grassmann Class Representation
Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class RepresentationIEEE International Conference on Computer Vision (ICCV), 2023
Haoqi Wang
Zhizhong Li
Wayne Zhang
274
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03 Aug 2023
RAYEN: Imposition of Hard Convex Constraints on Neural Networks
RAYEN: Imposition of Hard Convex Constraints on Neural Networks
J. Tordesillas
Jonathan P. How
Marco Hutter
193
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17 Jul 2023
Stabilized Neural Differential Equations for Learning Dynamics with
  Explicit Constraints
Stabilized Neural Differential Equations for Learning Dynamics with Explicit ConstraintsNeural Information Processing Systems (NeurIPS), 2023
Alistair J R White
Niki Kilbertus
Maximilian Gelbrecht
Niklas Boers
450
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16 Jun 2023
Exploiting Noise as a Resource for Computation and Learning in Spiking
  Neural Networks
Exploiting Noise as a Resource for Computation and Learning in Spiking Neural Networks
Gehua (Marcus) Ma
Rui Yan
Huajin Tang
548
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0
25 May 2023
A Study of Neural Collapse Phenomenon: Grassmannian Frame, Symmetry and
  Generalization
A Study of Neural Collapse Phenomenon: Grassmannian Frame, Symmetry and Generalization
Peifeng Gao
Qianqian Xu
Peisong Wen
Huiyang Shao
Zhiyong Yang
Qingming Huang
340
10
0
18 Apr 2023
Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms
  for Optimization under Orthogonality Constraints
Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms for Optimization under Orthogonality Constraints
Pierre Ablin
Simon Vary
Bin Gao
P.-A. Absil
226
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0
29 Mar 2023
Unsupervised Interpretable Basis Extraction for Concept-Based Visual Explanations
Unsupervised Interpretable Basis Extraction for Concept-Based Visual ExplanationsIEEE Transactions on Artificial Intelligence (IEEE TAI), 2023
Alexandros Doumanoglou
S. Asteriadis
D. Zarpalas
FAttSSL
315
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19 Mar 2023
Uncovering Challenges of Solving the Continuous Gromov-Wasserstein Problem
Uncovering Challenges of Solving the Continuous Gromov-Wasserstein Problem
Xavier Aramayo Carrasco
Maksim Nekrashevich
Petr Mokrov
Evgeny Burnaev
Alexander Korotin
OT
671
7
0
10 Mar 2023
Bootstrapping Parallel Anchors for Relative Representations
Bootstrapping Parallel Anchors for Relative Representations
Irene Cannistraci
Luca Moschella
Valentino Maiorca
Marco Fumero
Antonio Norelli
Emanuele Rodolà
357
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01 Mar 2023
Simplifying Momentum-based Positive-definite Submanifold Optimization
  with Applications to Deep Learning
Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep LearningInternational Conference on Machine Learning (ICML), 2023
Wu Lin
Valentin Duruisseaux
Melvin Leok
Frank Nielsen
Mohammad Emtiyaz Khan
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614
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20 Feb 2023
Deep networks for system identification: a Survey
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G. Pillonetto
Aleksandr Aravkin
Daniel Gedon
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Antônio H. Ribeiro
Thomas B. Schon
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Gated Recurrent Neural Networks with Weighted Time-Delay Feedback
Gated Recurrent Neural Networks with Weighted Time-Delay FeedbackInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
N. Benjamin Erichson
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354
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Multi-View Independent Component Analysis with Shared and Individual
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Multi-View Independent Component Analysis with Shared and Individual SourcesConference on Uncertainty in Artificial Intelligence (UAI), 2022
T. Pandeva
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398
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Random orthogonal additive filters: a solution to the
  vanishing/exploding gradient of deep neural networks
Random orthogonal additive filters: a solution to the vanishing/exploding gradient of deep neural networksIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Andrea Ceni
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224
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Feedback Gradient Descent: Efficient and Stable Optimization with
  Orthogonality for DNNs
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNsAAAI Conference on Artificial Intelligence (AAAI), 2022
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253
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Path Development Network with Finite-dimensional Lie Group
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285
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Geometry-Aware Supertagging with Heterogeneous Dynamic Convolutions
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277
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Yingjie Liu
Xian Wei
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247
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Contrastive Laplacian Eigenmaps
Contrastive Laplacian EigenmapsNeural Information Processing Systems (NeurIPS), 2022
Hao Zhu
Ke Sun
Piotr Koniusz
299
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Nested Hyperbolic Spaces for Dimensionality Reduction and Hyperbolic NN
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Xiran Fan
Chun-Hao Yang
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249
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Deep Decomposition for Stochastic Normal-Abnormal Transport
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Yueh Z. Lee
S. Aylward
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217
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Modeling Irregular Time Series with Continuous Recurrent Units
Modeling Irregular Time Series with Continuous Recurrent UnitsInternational Conference on Machine Learning (ICML), 2021
Mona Schirmer
Mazin Eltayeb
Stefan Lessmann
Maja R. Rudolph
BDLAI4TS
482
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How Does Momentum Benefit Deep Neural Networks Architecture Design? A
  Few Case Studies
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T. Nguyen
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Long Expressive Memory for Sequence Modeling
Long Expressive Memory for Sequence ModelingInternational Conference on Learning Representations (ICLR), 2021
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524
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Oscillatory Fourier Neural Network: A Compact and Efficient Architecture
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202
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Coordinate descent on the orthogonal group for recurrent neural network
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