On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport

24 May 2018

Papers citing "On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport"

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Title
Convergence of Time-Averaged Mean Field Gradient Descent Dynamics for Continuous Multi-Player Zero-Sum Games Yulong Lu Pierre Monmarché MLT 34 0 0 12 May 2025
Ergodic Generative Flows Leo Maxime Brunswic Mateo Clemente Rui Heng Yang Adam Sigal Amir Rasouli Yinchuan Li 42 0 0 06 May 2025
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime Francesco Camilli D. Tieplova Eleonora Bergamin Jean Barbier 109 0 0 06 May 2025
Mirror Mean-Field Langevin Dynamics Anming Gu Juno Kim 31 0 0 05 May 2025
Don't be lazy: CompleteP enables compute-efficient deep transformers Nolan Dey Bin Claire Zhang Lorenzo Noci Mufan Bill Li Blake Bordelon Shane Bergsma C. Pehlevan Boris Hanin Joel Hestness 39 0 0 02 May 2025
Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime Raphael Barboni Gabriel Peyré François-Xavier Vialard MLT 34 0 0 25 Apr 2025
An overview of condensation phenomenon in deep learning Zhi-Qin John Xu Yaoyu Zhang Zhangchen Zhou AI4CE 29 0 0 13 Apr 2025
Statistically guided deep learning Michael Kohler A. Krzyżak ODL BDL 76 0 0 11 Apr 2025
Fractal and Regular Geometry of Deep Neural Networks Simmaco Di Lillo Domenico Marinucci Michele Salvi S. Vigogna MDE AI4CE 36 0 0 08 Apr 2025
Survey on Algorithms for multi-index models Joan Bruna Daniel Hsu 31 0 0 07 Apr 2025
Towards Understanding the Optimization Mechanisms in Deep Learning Binchuan Qi Wei Gong Li Li 47 0 0 29 Mar 2025
Beyond Propagation of Chaos: A Stochastic Algorithm for Mean Field Optimization Chandan Tankala Dheeraj M. Nagaraj Anant Raj 44 0 0 17 Mar 2025
The Spectral Bias of Shallow Neural Network Learning is Shaped by the Choice of Non-linearity Justin Sahs Ryan Pyle Fabio Anselmi Ankit B. Patel 60 0 0 13 Mar 2025
Global Convergence and Rich Feature Learning in $L$ -Layer Infinite-Width Neural Networks under $μ$ P Parametrization Zixiang Chen Greg Yang Qingyue Zhao Q. Gu MLT 50 0 0 12 Mar 2025
A Theory of Initialisation's Impact on Specialisation Devon Jarvis Sebastian Lee Clémentine Dominé Andrew M. Saxe Stefano Sarao Mannelli CLL 72 2 0 04 Mar 2025
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows Jonathan Geuter Clément Bonet Anna Korba David Alvarez-Melis 61 0 0 03 Mar 2025
Convergence of Shallow ReLU Networks on Weakly Interacting Data Léo Dana Francis R. Bach Loucas Pillaud-Vivien MLT 52 1 0 24 Feb 2025
A Gap Between the Gaussian RKHS and Neural Networks: An Infinite-Center Asymptotic Analysis Akash Kumar Rahul Parhi Mikhail Belkin 46 0 0 22 Feb 2025
Properties of Wasserstein Gradient Flows for the Sliced-Wasserstein Distance Christophe Vauthier Quentin Mérigot Anna Korba 45 0 0 10 Feb 2025
Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble Atsushi Nitanda Anzelle Lee Damian Tan Xing Kai Mizuki Sakaguchi Taiji Suzuki AI4CE 61 1 0 09 Feb 2025
Curse of Dimensionality in Neural Network Optimization Sanghoon Na Haizhao Yang 56 0 0 07 Feb 2025
Geometry and Optimization of Shallow Polynomial Networks Yossi Arjevani Joan Bruna Joe Kileel Elzbieta Polak Matthew Trager 36 1 0 10 Jan 2025
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input Ziang Chen Rong Ge MLT 61 1 0 10 Jan 2025
Non-geodesically-convex optimization in the Wasserstein space Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Petrus Mikkola Marcelo Hartmann Kai Puolamaki Arto Klami 53 2 0 08 Jan 2025
Linear convergence of proximal descent schemes on the Wasserstein space Razvan-Andrei Lascu Mateusz B. Majka David Siska Łukasz Szpruch 74 1 0 22 Nov 2024
Proportional infinite-width infinite-depth limit for deep linear neural networks Federico Bassetti Lucia Ladelli P. Rotondo 75 1 0 22 Nov 2024
Emergence of meta-stable clustering in mean-field transformer models Giuseppe Bruno Federico Pasqualotto Andrea Agazzi 45 6 0 30 Oct 2024
A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities Yatin Dandi Luca Pesce Hugo Cui Florent Krzakala Yue M. Lu Bruno Loureiro MLT 37 1 0 24 Oct 2024
Robust Feature Learning for Multi-Index Models in High Dimensions Alireza Mousavi-Hosseini Adel Javanmard Murat A. Erdogdu OOD AAML 44 1 0 21 Oct 2024
A Lipschitz spaces view of infinitely wide shallow neural networks Francesca Bartolucci Marcello Carioni José A. Iglesias Yury Korolev Emanuele Naldi S. Vigogna 23 0 0 18 Oct 2024
Loss Landscape Characterization of Neural Networks without Over-Parametrization Rustem Islamov Niccolò Ajroldi Antonio Orvieto Aurelien Lucchi 35 4 0 16 Oct 2024
Shallow diffusion networks provably learn hidden low-dimensional structure Nicholas M. Boffi Arthur Jacot Stephen Tu Ingvar M. Ziemann DiffM 36 1 0 15 Oct 2024
Kinetic interacting particle system: parameter estimation from complete and partial discrete observations Chiara Amorino Vytaut.e Pilipauskait.e 21 1 0 14 Oct 2024
Extended convexity and smoothness and their applications in deep learning Binchuan Qi Wei Gong Li Li 61 0 0 08 Oct 2024
The Optimization Landscape of SGD Across the Feature Learning Strength Alexander B. Atanasov Alexandru Meterez James B. Simon C. Pehlevan 43 2 0 06 Oct 2024
LoGra-Med: Long Context Multi-Graph Alignment for Medical Vision-Language Model Duy M. H. Nguyen N. T. Diep Trung Q. Nguyen Hoang-Bao Le Tai Nguyen ... Pengtao Xie Roger Wattenhofer James Zhou Daniel Sonntag Mathias Niepert VLM 55 3 0 03 Oct 2024
Simplicity bias and optimization threshold in two-layer ReLU networks Etienne Boursier Nicolas Flammarion 31 2 0 03 Oct 2024
Nonuniform random feature models using derivative information Konstantin Pieper Zezhong Zhang Guannan Zhang 14 2 0 03 Oct 2024
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory Francesco Mori Stefano Sarao Mannelli Francesca Mignacco 36 3 0 26 Sep 2024
Optimal sequencing depth for single-cell RNA-sequencing in Wasserstein space Jakwang Kim Sharvaj Kubal Geoffrey Schiebinger 24 1 0 22 Sep 2024
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks Clémentine Dominé Nicolas Anguita A. Proca Lukas Braun D. Kunin P. Mediano Andrew M. Saxe 38 3 0 22 Sep 2024
Graph Classification with GNNs: Optimisation, Representation and Inductive Bias P. Krishna Kumar a H. G. Ramaswamy 29 0 0 17 Aug 2024
Absence of Closed-Form Descriptions for Gradient Flow in Two-Layer Narrow Networks Yeachan Park AI4CE 25 0 0 15 Aug 2024
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics Alireza Mousavi-Hosseini Denny Wu Murat A. Erdogdu MLT AI4CE 35 6 0 14 Aug 2024
A spring-block theory of feature learning in deep neural networks Chengzhi Shi Liming Pan Ivan Dokmanić AI4CE 40 1 0 28 Jul 2024
On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries Nirmit Joshi Theodor Misiakiewicz Nathan Srebro 26 6 0 08 Jul 2024
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning Arthur Jacot Seok Hoan Choi Yuxiao Wen AI4CE 91 2 0 08 Jul 2024
Prospective Messaging: Learning in Networks with Communication Delays Ryan Fayyazi Christian Weilbach Frank D. Wood 25 0 0 07 Jul 2024
Precise analysis of ridge interpolators under heavy correlations -- a Random Duality Theory view Mihailo Stojnic 27 1 0 13 Jun 2024
Ridge interpolators in correlated factor regression models -- exact risk analysis Mihailo Stojnic 20 1 0 13 Jun 2024