Cover Image

Quadratic Objective Perturbation: Curvature-Based Differential Privacy

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cortild, Daniel, Cartis, Coralia
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Stochastic Krasnoselskii-Mann Iterations: Convergence without Uniformly Bounded Variance
by: Cortild, Daniel, et al.
Published: (2026)

A Parameter-Free First-Order Algorithm for Non-Convex Optimization with $\tilde{\mkern1mu O}(ε^{-5/3})$ Global Rate
by: Xiong, Sichao, et al.
Published: (2026)

Randomized Subspace Derivative-Free Optimization with Quadratic Models and Second-Order Convergence
by: Cartis, Coralia, et al.
Published: (2024)

Random Subspace Cubic-Regularization Methods, with Applications to Low-Rank Functions
by: Cartis, Coralia, et al.
Published: (2025)

Nonlinear Dimensionality Reduction Techniques for Bayesian Optimization
by: Long, Luo, et al.
Published: (2025)

Dimensionality Reduction Techniques for Global Bayesian Optimisation
by: Long, Luo, et al.
Published: (2024)

Scalable Second-Order Optimization Algorithms for Minimizing Low-rank Functions
by: Tansley, Edward, et al.
Published: (2025)

Bias-Optimal Bounds for SGD: A Computer-Aided Lyapunov Analysis
by: Cortild, Daniel, et al.
Published: (2025)

On Global Rates for Regularization Methods based on Secant Derivative Approximations
by: Cartis, Coralia, et al.
Published: (2025)

Second-order methods for quartically-regularised cubic polynomials, with applications to high-order tensor methods
by: Cartis, Coralia, et al.
Published: (2023)

Global Optimality Characterizations and Algorithms for Minimizing Quartically-Regularized Third-Order Taylor Polynomials
by: Zhu, Wenqi, et al.
Published: (2025)

Global Convergence of High-Order Regularization Methods with Sums-of-Squares Taylor Models
by: Zhu, Wenqi, et al.
Published: (2024)

Tensor-based Dinkelbach method for computing generalized tensor eigenvalues and its applications
by: Chen, Haibin, et al.
Published: (2025)

Online Optimization on Hadamard Manifolds: Curvature Independent Regret Bounds on Horospherically Convex Objectives
by: Sahinoglu, Emre, et al.
Published: (2025)

Differentiation Through Black-Box Quadratic Programming Solvers
by: Magoon, Connor W., et al.
Published: (2024)

Learning the subspace of variation for global optimization of functions with low effective dimension
by: Cartis, Coralia, et al.
Published: (2024)

Communication-Efficient Distributed Learning with Differential Privacy
by: Ren, Xiaoxing, et al.
Published: (2026)

A Penalty Approach for Differentiation Through Black-Box Quadratic Programming Solvers
by: Linghu, Yuxuan, et al.
Published: (2026)

Registration of algebraic varieties using Riemannian optimization
by: Goyens, Florentin, et al.
Published: (2024)

Double Momentum and Error Feedback for Clipping with Fast Rates and Differential Privacy
by: Islamov, Rustem, et al.
Published: (2025)

Aligned Multi Objective Optimization
by: Efroni, Yonathan, et al.
Published: (2025)

Expressivity of Quadratic Neural ODEs
by: Hanson, Joshua, et al.
Published: (2025)

Insights on Muon from Simple Quadratics
by: Gonon, Antoine, et al.
Published: (2026)

Chebyshev Center-Based Direction Selection for Multi-Objective Optimization and Training PINNs
by: Yoon, Hoyeol, et al.
Published: (2026)

Multi-Objective Optimization-Based Anonymization of Structured Data for Machine Learning Application
by: Wei, Yusi, et al.
Published: (2025)

Differential Privacy via Distributionally Robust Optimization
by: Selvi, Aras, et al.
Published: (2023)

On the Effectiveness of the z-Transform Method in Quadratic Optimization
by: Bach, Francis
Published: (2025)

Tight Rates for Bandit Control Beyond Quadratics
by: Sun, Y. Jennifer, et al.
Published: (2024)

Accelerated Optimization Landscape of Linear-Quadratic Regulator
by: Feng, Lechen, et al.
Published: (2023)

Statistical Robustness of Interval CVaR Based Regression Models under Perturbation and Contamination
by: You, Yulei, et al.
Published: (2026)

Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization
by: Dong, Youran, et al.
Published: (2025)

The Optimality of (Accelerated) SGD for High-Dimensional Quadratic Optimization
by: Zhang, Haihan, et al.
Published: (2024)

Quadratic models for understanding catapult dynamics of neural networks
by: Zhu, Libin, et al.
Published: (2022)

Distributionally Robust Multi-Objective Optimization
by: Yang, Yufeng, et al.
Published: (2026)

Preferential Multi-Objective Bayesian Optimization
by: Astudillo, Raul, et al.
Published: (2024)

Krasnoselskii-Mann Iterations: Inertia, Perturbations and Approximation
by: Cortild, Daniel, et al.
Published: (2024)

Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function
by: Mhanna, Elissa, et al.
Published: (2024)

Learning Decentralized Linear Quadratic Regulators with $\sqrt{T}$ Regret
by: Ye, Lintao, et al.
Published: (2022)

ML-Guided Primal Heuristics for Mixed Binary Quadratic Programs
by: Huang, Weimin, et al.
Published: (2026)

Fast Policy Learning for Linear Quadratic Control with Entropy Regularization
by: Guo, Xin, et al.
Published: (2023)