Junhong Lin

发表

Compressed Data Separation With Redundant Dictionaries

Song Li, Yi Shen, Junhong Lin, 2013, IEEE Transactions on Information Theory.

Optimal rates for spectral algorithms with least-squares regression over Hilbert spaces

Volkan Cevher, Lorenzo Rosasco, Alessandro Rudi, 2018, Applied and Computational Harmonic Analysis.

Optimal Learning for Multi-pass Stochastic Gradient Methods

Lorenzo Rosasco, Junhong Lin, L. Rosasco, 2016, NIPS.

Kernel Conjugate Gradient Methods with Random Projections pdf

Volkan Cevher, Junhong Lin, V. Cevher, 2018, ArXiv.

Generalization Properties and Implicit Regularization for Multiple Passes SGM

Lorenzo Rosasco, Junhong Lin, Raffaello Camoriano, 2016, ICML.

Online Learning Algorithms Can Converge Comparably Fast as Batch Learning

Ding-Xuan Zhou, Junhong Lin, Ding-Xuan Zhou, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Iterative Regularization for Learning with Convex Loss Functions

Lorenzo Rosasco, Ding-Xuan Zhou, Junhong Lin, 2015, J. Mach. Learn. Res..

Sparse Recovery with Coherent Tight Frame via Analysis Dantzig Selector and Analysis LASSO pdf

Song Li, Junhong Lin, Junhong Lin, 2013, ArXiv.

Online pairwise learning algorithms with convex loss functions

Bo Zhang, Yunwen Lei, Ding-Xuan Zhou, 2017, Inf. Sci..

Generalization Properties of Doubly Online Learning Algorithms

Lorenzo Rosasco, Junhong Lin, 2018, J. Complex..

Compressed Sensing with coherent tight frames via $l_q$-minimization for $0 pdf

Song Li, Junhong Lin, Junhong Lin, 2011, ArXiv.

Chemical machine learning with kernels: The impact of loss functions

Volkan Cevher, Junhong Lin, Quang Van Nguyen, 2019, International Journal of Quantum Chemistry.

Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods

Volkan Cevher, Junhong Lin, V. Cevher, 2018, ICML.

Modified Fejér sequences and applications

Lorenzo Rosasco, Silvia Villa, Ding-Xuan Zhou, 2015, Computational Optimization and Applications.

A Learning-Based Framework for Quantized Compressed Sensing

Volkan Cevher, Rabeeh Karimi Mahabadi, Junhong Lin, 2019, IEEE Signal Processing Letters.

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

Volkan Cevher, Junhong Lin, 2018, ArXiv.

Restricted q-Isometry Properties Adapted to Frames for Nonconvex lq-Analysis

Song Li, Junhong Lin, Junhong Lin, 2016, IEEE Trans. Inf. Theory.

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

Volkan Cevher, Junhong Lin, V. Cevher, 2018, ICML.

Optimal Rates for Multi-pass Stochastic Gradient Methods

Lorenzo Rosasco, Junhong Lin, L. Rosasco, 2016, J. Mach. Learn. Res..

Learning theory of randomized Kaczmarz algorithm

Ding-Xuan Zhou, Junhong Lin, Ding-Xuan Zhou, 2015, J. Mach. Learn. Res..

Indoor Localization Based on Weighted Surfacing from Crowdsourced Samples

Guang Yang, Mu Zhou, Bang Wang, 2018, Sensors.

Optimal Rates for Learning with Nyström Stochastic Gradient Methods pdf

Lorenzo Rosasco, Junhong Lin, 2017, ArXiv.

Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections

Volkan Cevher, Junhong Lin, V. Cevher, 2020, J. Mach. Learn. Res..

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

Volkan Cevher, Junhong Lin, V. Cevher, 2018, ArXiv.

New Bounds for Restricted Isometry Constants With Coherent Tight Frames

Song Li, Yi Shen, Junhong Lin, 2013, IEEE Transactions on Signal Processing.

Nonuniform support recovery from noisy random measurements by Orthogonal Matching Pursuit

Song Li, Junhong Lin, Junhong Lin, 2013, J. Approx. Theory.

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

Volkan Cevher, Junhong Lin, V. Cevher, 2018, J. Mach. Learn. Res..