Junhong Lin
13 papers · 2015–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π§ Keyword Pioneer π£ Hot Topic Early Bird π Cross-Pollinator (11) πΊοΈ Taxonomy Completionist (15)
π
Conference Polyglot
(5)
π
Academic Marathon
(10)
π
Keyword Champion
(4)
π
Century Club
(13)
Conferences
JMLR (5)
ICML (4)
NIPS (2)
ICLR (1)
UAI (1)
Top co-authors
Keywords
stochastic gradient descent
(5)
reproducing kernel hilbert space
(5)
convergence rate
(4)
stochastic gradient method
(4)
least squares regression
(3)
early stopping
(3)
distributed learning
(2)
regularized algorithm
(2)
regularization parameter
(2)
learning rate
(2)
generalization bound
(1)
random projection
(1)
spectral algorithm
(1)
adam optimizer
(1)
polyadic noise
(1)
implicit regularization
(1)
subgradient method
(1)
convex loss function
(1)
generalization property
(1)
adaptive gradient descent
(1)
Papers
Reasoning of Large Language Models over Knowledge Graphs with Super-Relations
ICLR 2025
LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
ICML 2025
Revisiting Convergence of AdaGrad with Relaxed Assumptions
UAI 2024
On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions
NIPS 2024
Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections
JMLR 2020
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms
JMLR 2020
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods
ICML 2018
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces
ICML 2018
Optimal Rates for Multi-pass Stochastic Gradient Methods
JMLR 2017
Optimal Learning for Multi-pass Stochastic Gradient Methods
NIPS 2016
Generalization Properties and Implicit Regularization for Multiple Passes SGM
ICML 2016
Iterative Regularization for Learning with Convex Loss Functions
JMLR 2016
Learning Theory of Randomized Kaczmarz Algorithm
JMLR 2015