Dealing with unbounded gradients in stochastic saddle-point optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Neu, Gergely, Okolo, Nneka |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Offline RL via Feature-Occupancy Gradient Ascent
by: Neu, Gergely, et al.
Published: (2024)
by: Neu, Gergely, et al.
Published: (2024)
A stochastic gradient method for trilevel optimization
by: Giovannelli, Tommaso, et al.
Published: (2025)
by: Giovannelli, Tommaso, et al.
Published: (2025)
Avoiding strict saddle points of nonconvex regularized problems
by: Bai, Luwei, et al.
Published: (2024)
by: Bai, Luwei, et al.
Published: (2024)
Unregularized limit of stochastic gradient method for Wasserstein distributionally robust optimization
by: Le, Tam
Published: (2025)
by: Le, Tam
Published: (2025)
Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach
by: Dirren, Colin, et al.
Published: (2024)
by: Dirren, Colin, et al.
Published: (2024)
Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
by: Calo, Sergio, et al.
Published: (2024)
by: Calo, Sergio, et al.
Published: (2024)
Projected gradient methods for nonconvex and stochastic smooth optimization: new complexities and auto-conditioned stepsizes
by: Lan, Guanghui, et al.
Published: (2024)
by: Lan, Guanghui, et al.
Published: (2024)
Almost sure convergence rates of stochastic gradient methods under gradient domination
by: Weissmann, Simon, et al.
Published: (2024)
by: Weissmann, Simon, et al.
Published: (2024)
Generalized EXTRA stochastic gradient Langevin dynamics
by: Gurbuzbalaban, Mert, et al.
Published: (2024)
by: Gurbuzbalaban, Mert, et al.
Published: (2024)
New logarithmic step size for stochastic gradient descent
by: Shamaee, M. Soheil, et al.
Published: (2024)
by: Shamaee, M. Soheil, et al.
Published: (2024)
Non-convergence to global minimizers for Adam and stochastic gradient descent optimization and constructions of local minimizers in the training of artificial neural networks
by: Jentzen, Arnulf, et al.
Published: (2024)
by: Jentzen, Arnulf, et al.
Published: (2024)
Instance-optimal stochastic convex optimization: Can we improve upon sample-average and robust stochastic approximation?
by: Jiang, Liwei, et al.
Published: (2026)
by: Jiang, Liwei, et al.
Published: (2026)
Flattened one-bit stochastic gradient descent: compressed distributed optimization with controlled variance
by: Stollenwerk, Alexander, et al.
Published: (2024)
by: Stollenwerk, Alexander, et al.
Published: (2024)
Online estimation of the inverse of the Hessian for stochastic optimization with application to universal stochastic Newton algorithms
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)
Variance reduction techniques for stochastic proximal point algorithms
by: Traoré, Cheik, et al.
Published: (2023)
by: Traoré, Cheik, et al.
Published: (2023)
Convergence of continuous-time stochastic gradient descent with applications to deep neural networks
by: Lugosi, Gabor, et al.
Published: (2024)
by: Lugosi, Gabor, et al.
Published: (2024)
Primal-dual algorithm for contextual stochastic combinatorial optimization
by: Bouvier, Louis, et al.
Published: (2025)
by: Bouvier, Louis, et al.
Published: (2025)
Convergence rates of stochastic gradient method with independent sequences of step-size and momentum weight
by: Hwang, Wen-Liang
Published: (2024)
by: Hwang, Wen-Liang
Published: (2024)
Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient
by: Lim, Dong-Young, et al.
Published: (2022)
by: Lim, Dong-Young, et al.
Published: (2022)
A stochastic gradient descent algorithm with random search directions
by: Gbaguidi, Eméric
Published: (2025)
by: Gbaguidi, Eméric
Published: (2025)
Convergence of stochastic gradient descent under a local Lojasiewicz condition for deep neural networks
by: An, Jing, et al.
Published: (2023)
by: An, Jing, et al.
Published: (2023)
Model approximation in MDPs with unbounded per-step cost
by: Bozkurt, Berk, et al.
Published: (2024)
by: Bozkurt, Berk, et al.
Published: (2024)
The generator gradient estimator is an adjoint state method for stochastic differential equations
by: Badolle, Quentin, et al.
Published: (2024)
by: Badolle, Quentin, et al.
Published: (2024)
Beyond adaptive gradient: Fast-Controlled Minibatch Algorithm for large-scale optimization
by: Coppola, Corrado, et al.
Published: (2024)
by: Coppola, Corrado, et al.
Published: (2024)
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms
by: Dagréou, Mathieu, et al.
Published: (2022)
by: Dagréou, Mathieu, et al.
Published: (2022)
Adaptive multi-gradient methods for quasiconvex vector optimization and applications to multi-task learning
by: Minh, Nguyen Anh, et al.
Published: (2024)
by: Minh, Nguyen Anh, et al.
Published: (2024)
Solving a class of stochastic optimal control problems by physics-informed neural networks
by: Jiao, Zhe, et al.
Published: (2024)
by: Jiao, Zhe, et al.
Published: (2024)
A learning-based approach to stochastic optimal control under reach-avoid constraint
by: Ni, Tingting, et al.
Published: (2024)
by: Ni, Tingting, et al.
Published: (2024)
Mean-square and linear convergence of a stochastic proximal point algorithm in metric spaces of nonpositive curvature
by: Pischke, Nicholas
Published: (2025)
by: Pischke, Nicholas
Published: (2025)
Learning rate adaptive stochastic gradient descent optimization methods: numerical simulations for deep learning methods for partial differential equations and convergence analyses
by: Dereich, Steffen, et al.
Published: (2024)
by: Dereich, Steffen, et al.
Published: (2024)
On improving generalization in a class of learning problems with the method of small parameters for weakly-controlled optimal gradient systems
by: Befekadu, Getachew K.
Published: (2024)
by: Befekadu, Getachew K.
Published: (2024)
You Shall Pass: Dealing with the Zero-Gradient Problem in Predict and Optimize for Convex Optimization
by: Veviurko, Grigorii, et al.
Published: (2023)
by: Veviurko, Grigorii, et al.
Published: (2023)
An inexact Bregman proximal point method and its acceleration version for unbalanced optimal transport
by: Chen, Xiang, et al.
Published: (2024)
by: Chen, Xiang, et al.
Published: (2024)
On propagation of chaos for the Fisher-Rao gradient flow in entropic mean-field optimization
by: Lazić, Petra, et al.
Published: (2026)
by: Lazić, Petra, et al.
Published: (2026)
A stochastic smoothing framework for nonconvex-nonconcave min-sum-max problems with applications to Wasserstein distributionally robust optimization
by: Liu, Wei, et al.
Published: (2025)
by: Liu, Wei, et al.
Published: (2025)
Convergence of projected stochastic natural gradient variational inference for various step size and sample or batch size schedules
by: Guilmeau, Thomas, et al.
Published: (2026)
by: Guilmeau, Thomas, et al.
Published: (2026)
On the convergence of conditional gradient method for unbounded multiobjective optimization problems
by: Chen, Wang, et al.
Published: (2024)
by: Chen, Wang, et al.
Published: (2024)
Non-asymptotic convergence analysis of the stochastic gradient Hamiltonian Monte Carlo algorithm with discontinuous stochastic gradient with applications to training of ReLU neural networks
by: Liang, Luxu, et al.
Published: (2024)
by: Liang, Luxu, et al.
Published: (2024)
Proximal gradient descent on the smoothed duality gap to solve saddle point problems
by: Fercoq, Olivier
Published: (2025)
by: Fercoq, Olivier
Published: (2025)
A theoretical and empirical study of new adaptive algorithms with additional momentum steps and shifted updates for stochastic non-convex optimization
by: Alecsa, Cristian Daniel
Published: (2021)
by: Alecsa, Cristian Daniel
Published: (2021)
Similar Items
-
Offline RL via Feature-Occupancy Gradient Ascent
by: Neu, Gergely, et al.
Published: (2024) -
A stochastic gradient method for trilevel optimization
by: Giovannelli, Tommaso, et al.
Published: (2025) -
Avoiding strict saddle points of nonconvex regularized problems
by: Bai, Luwei, et al.
Published: (2024) -
Unregularized limit of stochastic gradient method for Wasserstein distributionally robust optimization
by: Le, Tam
Published: (2025) -
Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach
by: Dirren, Colin, et al.
Published: (2024)