Saved in:
| Main Authors: | Klochkov, Yegor, Liu, Yang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.17357 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A mean teacher algorithm for unlearning of language models
by: Klochkov, Yegor
Published: (2025)
by: Klochkov, Yegor
Published: (2025)
Post-hoc Bias Scoring Is Optimal For Fair Classification
by: Chen, Wenlong, et al.
Published: (2023)
by: Chen, Wenlong, et al.
Published: (2023)
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment
by: Liu, Yang, et al.
Published: (2023)
by: Liu, Yang, et al.
Published: (2023)
Revisit, Extend, and Enhance Hessian-Free Influence Functions
by: Yang, Ziao, et al.
Published: (2024)
by: Yang, Ziao, et al.
Published: (2024)
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning
by: Elsayed, Mohamed, et al.
Published: (2024)
by: Elsayed, Mohamed, et al.
Published: (2024)
Revisiting Zeroth-Order Hessian Approximation: A Single-Step Policy Optimization Lens
by: Qiu, Junbin, et al.
Published: (2026)
by: Qiu, Junbin, et al.
Published: (2026)
Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models
by: Schaeffer, Rylan, et al.
Published: (2025)
by: Schaeffer, Rylan, et al.
Published: (2025)
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)
Spin glass to paramagnetic transition and triple point in Spherical SK model
by: Johnstone, Iain M., et al.
Published: (2021)
by: Johnstone, Iain M., et al.
Published: (2021)
Depth, Not Data: An Analysis of Hessian Spectral Bifurcation
by: Deng, Shenyang, et al.
Published: (2026)
by: Deng, Shenyang, et al.
Published: (2026)
SwiftPrune: Hessian-Free Weight Pruning for Large Language Models
by: Kang, Yuhan, et al.
Published: (2025)
by: Kang, Yuhan, et al.
Published: (2025)
HessFormer: Hessians at Foundation Scale
by: Granziol, Diego
Published: (2025)
by: Granziol, Diego
Published: (2025)
Hessian QM9: A quantum chemistry database of molecular Hessians in implicit solvents
by: Williams, Nicholas J., et al.
Published: (2024)
by: Williams, Nicholas J., et al.
Published: (2024)
Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization
by: Zhu, Zirui, et al.
Published: (2024)
by: Zhu, Zirui, et al.
Published: (2024)
Hessian-Informed Flow Matching
by: Sprague, Christopher Iliffe, et al.
Published: (2024)
by: Sprague, Christopher Iliffe, et al.
Published: (2024)
Hessian Spectral Analysis at Foundation Model Scale
by: Granziol, Diego, et al.
Published: (2026)
by: Granziol, Diego, et al.
Published: (2026)
The Hessian of tall-skinny networks is easy to invert
by: Rahimi, Ali
Published: (2026)
by: Rahimi, Ali
Published: (2026)
Constrained Bi-Level Optimization: Proximal Lagrangian Value function Approach and Hessian-free Algorithm
by: Yao, Wei, et al.
Published: (2024)
by: Yao, Wei, et al.
Published: (2024)
KV Cache Offloading for Context-Intensive Tasks
by: Bocharnikov, Andrey, et al.
Published: (2026)
by: Bocharnikov, Andrey, et al.
Published: (2026)
Hessian-Free Online Certified Unlearning
by: Qiao, Xinbao, et al.
Published: (2024)
by: Qiao, Xinbao, et al.
Published: (2024)
Stochastic Hessian Fittings with Lie Groups
by: Li, Xi-Lin
Published: (2024)
by: Li, Xi-Lin
Published: (2024)
Better Training Data Attribution via Better Inverse Hessian-Vector Products
by: Wang, Andrew, et al.
Published: (2025)
by: Wang, Andrew, et al.
Published: (2025)
Hessian Surgery: Class-Targeted Post-Hoc Rebalancing via Hessian Spike Perturbation
by: Vigna, Hugo, et al.
Published: (2026)
by: Vigna, Hugo, et al.
Published: (2026)
Neglected Hessian component explains mysteries in Sharpness regularization
by: Dauphin, Yann N., et al.
Published: (2024)
by: Dauphin, Yann N., et al.
Published: (2024)
Bayesian Influence Functions for Hessian-Free Data Attribution
by: Kreer, Philipp Alexander, et al.
Published: (2025)
by: Kreer, Philipp Alexander, et al.
Published: (2025)
Converge Faster, Talk Less: Hessian-Informed Federated Zeroth-Order Optimization
by: Li, Zhe, et al.
Published: (2025)
by: Li, Zhe, et al.
Published: (2025)
Community detection with the Bethe-Hessian
by: Stephan, Ludovic, et al.
Published: (2024)
by: Stephan, Ludovic, et al.
Published: (2024)
HEAPr: Hessian-based Efficient Atomic Expert Pruning in Output Space
by: Li, Ke, et al.
Published: (2025)
by: Li, Ke, et al.
Published: (2025)
Flow map learning in nonlinear vector autoregressive models: influence of the feature-library structure on the training error
by: Gross, Markus
Published: (2026)
by: Gross, Markus
Published: (2026)
The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank
by: Bar, Amitay, et al.
Published: (2024)
by: Bar, Amitay, et al.
Published: (2024)
Local Hessian Spectral Filtering for Robust Intrinsic Dimension Estimation
by: Osada, Genki
Published: (2026)
by: Osada, Genki
Published: (2026)
Moment Alignment: Unifying Gradient and Hessian Matching for Domain Generalization
by: Chen, Yuen, et al.
Published: (2025)
by: Chen, Yuen, et al.
Published: (2025)
A Hessian-informed hyperparameter optimization for differential learning rate
by: Xu, Shiyun, et al.
Published: (2025)
by: Xu, Shiyun, et al.
Published: (2025)
Shared active subspace for multivariate vector-valued functions
by: Musayeva, Khadija, et al.
Published: (2024)
by: Musayeva, Khadija, et al.
Published: (2024)
Gradient-Normalized Smoothness for Optimization with Approximate Hessians
by: Semenov, Andrei, et al.
Published: (2025)
by: Semenov, Andrei, et al.
Published: (2025)
Towards Quantifying the Hessian Structure of Neural Networks
by: Dong, Zhaorui, et al.
Published: (2025)
by: Dong, Zhaorui, et al.
Published: (2025)
Hessian Aware Low-Rank Perturbation for Order-Robust Continual Learning
by: Li, Jiaqi, et al.
Published: (2023)
by: Li, Jiaqi, et al.
Published: (2023)
The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks
by: Gabdullin, Nikita
Published: (2025)
by: Gabdullin, Nikita
Published: (2025)
Unraveling the Hessian: A Key to Smooth Convergence in Loss Function Landscapes
by: Kiselev, Nikita, et al.
Published: (2024)
by: Kiselev, Nikita, et al.
Published: (2024)
Connecting Parameter Magnitudes and Hessian Eigenspaces at Scale using Sketched Methods
by: Fernandez, Andres, et al.
Published: (2025)
by: Fernandez, Andres, et al.
Published: (2025)
Similar Items
-
A mean teacher algorithm for unlearning of language models
by: Klochkov, Yegor
Published: (2025) -
Post-hoc Bias Scoring Is Optimal For Fair Classification
by: Chen, Wenlong, et al.
Published: (2023) -
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment
by: Liu, Yang, et al.
Published: (2023) -
Revisit, Extend, and Enhance Hessian-Free Influence Functions
by: Yang, Ziao, et al.
Published: (2024) -
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning
by: Elsayed, Mohamed, et al.
Published: (2024)