Beilun Wang
12 papers · 2017–2026 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (29) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Research topics
Machine Learning
(7)
Optimization & Theory
(5)
Artificial Intelligence
(4)
Core Methods
(4)
Deep Learning
(3)
Mathematics & Optimization
(3)
Application Areas
(3)
Healthcare & Medicine
(2)
Architectures
(2)
Bayesian & Probabilistic
(2)
Learning Paradigms
(2)
Learning Types Β· Machine Learning
(2)
Learning Types Β· Deep Learning
(2)
Mathematics
(2)
Models
(2)
Keywords
gaussian graphical model
(3)
sparse estimation
(2)
high-dimensional estimation
(2)
high-dimensional statistics
(2)
mutual transfer learning
(2)
domain adaptation
(1)
data poisoning
(1)
active learning
(1)
covariance estimation
(1)
inverse covariance
(1)
graph representation
(1)
model selection
(1)
energy efficiency
(1)
membrane potential
(1)
precision matrix
(1)
feature selection
(1)
episodic memory
(1)
matrix completion
(1)
parameter estimation
(1)
multi-task learning
(1)
Papers
Compressing LLM Knowledge into Graph Representations for Text-attributed Graphs Learning
ACL 2026
LiGen: Active Lipid Generation via a Molecular Language Model
ACL 2026
Structured Episodic Event Memory
ACL 2026
Bi-perspective Splitting Defense: Achieving Clean-Seed-Free Backdoor Security
ICML 2025
ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks
IJCAI 2025
Adaptive Group Personalization for Federated Mutual Transfer Learning
ICML 2024
FasMe: Fast and Sample-efficient Meta Estimator for Precision Matrix Learning in Small Sample Settings
NeurIPS 2024
A Difference Standardization Method for Mutual Transfer Learning
ICML 2022
Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables
IJCAI 2020
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
ICML 2018
Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure
AISTATS 2018
A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models
AISTATS 2017