Haishan Ye

Orcid: 0000-0002-0242-4857

According to our database1, Haishan Ye authored at least 37 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer.
CoRR, 2024

2023
Intelligent Image Processing Technology for Badminton Robot under Machine Vision of Internet of Things.
Int. J. Humanoid Robotics, December, 2023

Accelerated Distributed Approximate Newton Method.
IEEE Trans. Neural Networks Learn. Syst., November, 2023

Towards explicit superlinear convergence rate for SR1.
Math. Program., May, 2023

PPFL: A Personalized Federated Learning Framework for Heterogeneous Population.
CoRR, 2023

Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold.
CoRR, 2023

Mirror Natural Evolution Strategies.
CoRR, 2023

Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Explicit Convergence Rates of Greedy and Random Quasi-Newton Methods.
J. Mach. Learn. Res., 2022

A Simple and Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization.
CoRR, 2022

An Optimal Stochastic Algorithm for Decentralized Nonconvex Finite-sum Optimization.
CoRR, 2022

Decentralized Stochastic Variance Reduced Extragradient Method.
CoRR, 2022

Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Accelerated Proximal Subsampled Newton Method.
IEEE Trans. Neural Networks Learn. Syst., 2021

DeEPCA: Decentralized Exact PCA with Linear Convergence Rate.
J. Mach. Learn. Res., 2021

Approximate Newton Methods.
J. Mach. Learn. Res., 2021

Greedy and Random Broyden's Methods with Explicit Superlinear Convergence Rates in Nonlinear Equations.
CoRR, 2021

Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear Convergence.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Nesterov's Acceleration for Approximate Newton.
J. Mach. Learn. Res., 2020

PMGT-VR: A decentralized proximal-gradient algorithmic framework with variance reduction.
CoRR, 2020

Multi-consensus Decentralized Accelerated Gradient Descent.
CoRR, 2020

Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems.
CoRR, 2020

Decentralized Accelerated Proximal Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Fast stochastic second-order method logarithmic in condition number.
Pattern Recognit., 2019

Fast Generalized Matrix Regression with Applications in Machine Learning.
CoRR, 2019

Mirror Natural Evolution Strategies.
CoRR, 2019

2018
Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack.
CoRR, 2018

2017
Fast Fisher discriminant analysis with randomized algorithms.
Pattern Recognit., 2017

Nesterov's Acceleration For Approximate Newton.
CoRR, 2017

A Unifying Framework for Convergence Analysis of Approximate Newton Methods.
CoRR, 2017

Approximate Newton Methods and Their Local Convergence.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Tighter bound of Sketched Generalized Matrix Approximation.
CoRR, 2016

Revisiting Sub-sampled Newton Methods.
CoRR, 2016

Accelerating Random Kaczmarz Algorithm Based on Clustering Information.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016


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