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Papers
Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
ICLR 2025
SwiftPrune: Hessian-Free Weight Pruning for Large Language Models
EMNLP 2025
Achieving O(ε^-1.5) Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization
NeurIPS 2023
On the Convergence Theory for Hessian-Free Bilevel Algorithms
NeurIPS 2022
Differentiable Likelihoods for Fast Inversion of ’Likelihood-Free’ Dynamical Systems
ICML 2020
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms
AISTATS 2020
A Generic Approach for Escaping Saddle points
AISTATS 2018
Combining Natural Gradient with Hessian Free Methods for Sequence Training
Interspeech 2018
Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification
ACML 2018
Second-Order Stochastic Optimization for Machine Learning in Linear Time
JMLR 2017
Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks
NeurIPS 2015