Variance-Reduced $(\varepsilon,δ)-$Unlearning using Forget Set Gradients
Fuente:
arXiv
Saved in:
| Main Authors: | Van Waerebeke, Martin, Lorenzi, Marco, Scaman, Kevin, Mhamdi, El Mahdi El, Neglia, Giovanni |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
When to Forget? Complexity Trade-offs in Machine Unlearning
by: Van Waerebeke, Martin, et al.
Published: (2025)
by: Van Waerebeke, Martin, et al.
Published: (2025)
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods
by: Chayti, El Mahdi, et al.
Published: (2023)
by: Chayti, El Mahdi, et al.
Published: (2023)
In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting
by: Philippenko, Constantin, et al.
Published: (2024)
by: Philippenko, Constantin, et al.
Published: (2024)
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
by: Fraboni, Yann, et al.
Published: (2022)
by: Fraboni, Yann, et al.
Published: (2022)
Byzantine Machine Learning: MultiKrum and an optimal notion of robustness
by: Bareilles, Gilles, et al.
Published: (2026)
by: Bareilles, Gilles, et al.
Published: (2026)
Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks
by: Robin, David A. R., et al.
Published: (2025)
by: Robin, David A. R., et al.
Published: (2025)
Stochastic Difference-of-Convex Optimization with Momentum
by: Chayti, El Mahdi, et al.
Published: (2025)
by: Chayti, El Mahdi, et al.
Published: (2025)
A Split-Client Approach to Second-Order Optimization
by: Chayti, El Mahdi, et al.
Published: (2025)
by: Chayti, El Mahdi, et al.
Published: (2025)
A New First-Order Meta-Learning Algorithm with Convergence Guarantees
by: Chayti, El Mahdi, et al.
Published: (2024)
by: Chayti, El Mahdi, et al.
Published: (2024)
Stochastic Compositional Optimization via Hybrid Momentum Frank--Wolfe
by: Chayti, El Mahdi
Published: (2026)
by: Chayti, El Mahdi
Published: (2026)
RanSOM: Second-Order Momentum with Randomized Scaling for Constrained and Unconstrained Optimization
by: Chayti, El Mahdi
Published: (2026)
by: Chayti, El Mahdi
Published: (2026)
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles
by: Scaman, Kevin, et al.
Published: (2023)
by: Scaman, Kevin, et al.
Published: (2023)
Faster Gradient Methods for Highly-Smooth Stochastic Bilevel Optimization
by: Chen, Lesi, et al.
Published: (2025)
by: Chen, Lesi, et al.
Published: (2025)
Stochastic Optimization with Random Search
by: Chayti, El Mahdi, et al.
Published: (2025)
by: Chayti, El Mahdi, et al.
Published: (2025)
Mitigating Forgetting in Continual Learning with Selective Gradient Projection
by: Singh, Anika, et al.
Published: (2026)
by: Singh, Anika, et al.
Published: (2026)
On the Stochastic (Variance-Reduced) Proximal Gradient Method for Regularized Expected Reward Optimization
by: Liang, Ling, et al.
Published: (2024)
by: Liang, Ling, et al.
Published: (2024)
Improving Stochastic Cubic Newton with Momentum
by: Chayti, El Mahdi, et al.
Published: (2024)
by: Chayti, El Mahdi, et al.
Published: (2024)
A Variance-Reduced Stochastic Gradient Tracking Algorithm for Decentralized Optimization with Orthogonality Constraints
by: Wang, Lei, et al.
Published: (2022)
by: Wang, Lei, et al.
Published: (2022)
VFOG: Variance-Reduced Fast Optimistic Gradient Methods for a Class of Nonmonotone Generalized Equations
by: Tran-Dinh, Quoc, et al.
Published: (2025)
by: Tran-Dinh, Quoc, et al.
Published: (2025)
Optimization with Access to Auxiliary Information
by: Chayti, El Mahdi, et al.
Published: (2022)
by: Chayti, El Mahdi, et al.
Published: (2022)
Stochastic Gradient Langevin Dynamics with Variance Reduction
by: Huang, Zhishen, et al.
Published: (2021)
by: Huang, Zhishen, et al.
Published: (2021)
A Rolling-Space Branch-and-Price Algorithm for the Multi-Compartment Vehicle Routing Problem with Multiple Time Windows
by: Raqabi, El Mehdi Er, et al.
Published: (2026)
by: Raqabi, El Mehdi Er, et al.
Published: (2026)
Controllable Machine Unlearning via Gradient Pivoting
by: Hwang, Youngsik, et al.
Published: (2025)
by: Hwang, Youngsik, et al.
Published: (2025)
Adaptive Optimization via Momentum on Variance-Normalized Gradients
by: Patitucci, Francisco, et al.
Published: (2026)
by: Patitucci, Francisco, et al.
Published: (2026)
Beyond Bounded Variance: Variance-Reduced Normalized Methods for Nonconvex Optimization under Blum-Gladyshev Noise
by: Upadhyay, Antesh, et al.
Published: (2026)
by: Upadhyay, Antesh, et al.
Published: (2026)
Gradient Estimation and Variance Reduction in Stochastic and Deterministic Models
by: Keane, Ronan
Published: (2024)
by: Keane, Ronan
Published: (2024)
Divergence Results and Convergence of a Variance Reduced Version of ADAM
by: Wang, Ruiqi, et al.
Published: (2022)
by: Wang, Ruiqi, et al.
Published: (2022)
Variance-Reduced Cascade Q-learning: Algorithms and Sample Complexity
by: Boveiri, Mohammad, et al.
Published: (2024)
by: Boveiri, Mohammad, et al.
Published: (2024)
Breaking the Stochasticity Barrier: An Adaptive Variance-Reduced Method for Variational Inequalities
by: Jeong, Yungi, et al.
Published: (2026)
by: Jeong, Yungi, et al.
Published: (2026)
Stochastic Variance-Reduced Newton: Accelerating Finite-Sum Minimization with Large Batches
by: Dereziński, Michał
Published: (2022)
by: Dereziński, Michał
Published: (2022)
Projected Forward Gradient-Guided Frank-Wolfe Algorithm via Variance Reduction
by: Rostami, M., et al.
Published: (2024)
by: Rostami, M., et al.
Published: (2024)
Global Convergence of Natural Policy Gradient with Hessian-aided Momentum Variance Reduction
by: Feng, Jie, et al.
Published: (2024)
by: Feng, Jie, et al.
Published: (2024)
Variance Reduction Methods Do Not Need to Compute Full Gradients: Improved Efficiency through Shuffling
by: Medyakov, Daniil, et al.
Published: (2025)
by: Medyakov, Daniil, et al.
Published: (2025)
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient
by: Di, Hao, et al.
Published: (2024)
by: Di, Hao, et al.
Published: (2024)
Truncated Variance Reduced Value Iteration
by: Jin, Yujia, et al.
Published: (2024)
by: Jin, Yujia, et al.
Published: (2024)
A Fair OR-ML Framework for Resource Substitution in Large-Scale Networks
by: Mohan, Ved, et al.
Published: (2025)
by: Mohan, Ved, et al.
Published: (2025)
Momentum Does Not Reduce Stochastic Noise in Stochastic Gradient Descent
by: Sato, Naoki, et al.
Published: (2024)
by: Sato, Naoki, et al.
Published: (2024)
Accelerated Stochastic ExtraGradient: Mixing Hessian and Gradient Similarity to Reduce Communication in Distributed and Federated Learning
by: Bylinkin, Dmitry, et al.
Published: (2024)
by: Bylinkin, Dmitry, et al.
Published: (2024)
Do Deep Networks Forget Initialization? A Forgetting-Time View of Practical Inductive Bias
by: Das, Mohua, et al.
Published: (2026)
by: Das, Mohua, et al.
Published: (2026)
Geometric Foundations of Tuning without Forgetting in Neural ODEs
by: Bayram, Erkan, et al.
Published: (2025)
by: Bayram, Erkan, et al.
Published: (2025)
Similar Items
-
When to Forget? Complexity Trade-offs in Machine Unlearning
by: Van Waerebeke, Martin, et al.
Published: (2025) -
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods
by: Chayti, El Mahdi, et al.
Published: (2023) -
In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting
by: Philippenko, Constantin, et al.
Published: (2024) -
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
by: Fraboni, Yann, et al.
Published: (2022) -
Byzantine Machine Learning: MultiKrum and an optimal notion of robustness
by: Bareilles, Gilles, et al.
Published: (2026)