Heng Lian
11 papers · 2018–2026 · 3 venues · across top CS/AI venues
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π Interdisciplinary Bridge Β· Bronze π Conference Polyglot Β· Bronze π Academic Marathon Β· Sprint πΊοΈ Taxonomy Completionist (24) π Keyword Champion (2)
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Research topics
Machine Learning
(11)
Core Methods
(11)
Optimization & Theory
(6)
Mathematics & Optimization
(4)
Mathematics
(3)
Optimization
(3)
Application Areas
(2)
Artificial Intelligence
(1)
Deep Learning
(1)
Architectures
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Learning Paradigms
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Learning Types Β· Machine Learning
(1)
Learning Types Β· Deep Learning
(1)
Statistics
(1)
Techniques
(1)
Keywords
quantile regression
(3)
distributed learning
(3)
variable selection
(2)
tucker decomposition
(2)
tensor decomposition
(2)
reproducing kernel hilbert space
(2)
semi-parametric model
(2)
support vector machine
(2)
empirical process
(2)
convergence rate
(2)
divide and conquer
(2)
covariate shift
(1)
curriculum learning
(1)
bregman divergence
(1)
feature selection
(1)
high-dimensional statistics
(1)
functional data analysis
(1)
sparse estimation
(1)
parameter estimation
(1)
nonparametric estimation
(1)
Papers
Kernel-based Distributed Learning
JMLR 2026
Metric-Agnostic Continual Learning for Sustainable Group Fairness
AAAI 2025
Optimal subsampling for high-dimensional partially linear models via machine learning methods
JMLR 2025
HGDL: Heterogeneous Graph Label Distribution Learning
NeurIPS 2024
More Efficient Estimation of Multivariate Additive Models Based on Tensor Decomposition and Penalization
JMLR 2024
Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions
JMLR 2022
Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space
NeurIPS 2022
Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification
JMLR 2022
High-dimensional quantile tensor regression
JMLR 2020
Ultra-High Dimensional Single-Index Quantile Regression
JMLR 2020
Divide-and-Conquer for Debiased l_1-norm Support Vector Machine in Ultra-high Dimensions
JMLR 2018