Junhong Lin

According to our database, Junhong Lin authored at least 10 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Convergence Theory of Sharpness-Aware Minimization With Interpolating Neural Networks.

Tan Sun, Yusu Hong, Junhong Lin

IEEE Trans. Signal Process., 2026

2024

PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network.

Tan Sun, Junhong Lin

CoRR, 2024

2020

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms.

Junhong Lin, Volkan Cevher

J. Mach. Learn. Res., 2020

Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections.

Junhong Lin, Volkan Cevher

J. Mach. Learn. Res., 2020

2019

A Learning-Based Framework for Quantized Compressed Sensing.

Rabeeh Karimi Mahabadi, Junhong Lin, Volkan Cevher

IEEE Signal Process. Lett., 2019

2018

Kernel Conjugate Gradient Methods with Random Projections.

Junhong Lin, Volkan Cevher

CoRR, 2018

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral-Regularization Algorithms.

Junhong Lin, Volkan Cevher

CoRR, 2018

Optimal Rates for Spectral-regularized Algorithms with Least-Squares Regression over Hilbert Spaces.

Junhong Lin, Volkan Cevher

CoRR, 2018

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces.

Junhong Lin, Volkan Cevher

Proceedings of the 35th International Conference on Machine Learning, 2018

Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods.

Junhong Lin, Volkan Cevher

Proceedings of the 35th International Conference on Machine Learning, 2018