Ziang Chen
13 papers · 2021–2026 · 6 venues · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (23) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Grand Slam
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Prolific Year Β· Productive
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Research topics
Machine Learning
(11)
Deep Learning
(9)
Optimization & Theory Β· Machine Learning
(9)
Architectures
(8)
Application Areas
(4)
Learning Types
(4)
Mathematics & Optimization
(3)
Core Methods
(3)
Artificial Intelligence
(2)
Core AI
(2)
Optimization & Theory Β· Deep Learning
(2)
Security & Privacy
(1)
Differential Privacy
(1)
Mathematics
(1)
Optimization
(1)
Keywords
graph neural network
(4)
stochastic gradient descent
(3)
optimal solution
(2)
machine unlearning
(2)
differential privacy
(2)
message passing
(2)
representation learning
(1)
langevin dynamics
(1)
model compression
(1)
mean field theory
(1)
mixed linear regression
(1)
non-convex optimization
(1)
probabilistic modeling
(1)
convex optimization
(1)
neural network theory
(1)
stochastic optimization
(1)
permutation equivariance
(1)
graph representation
(1)
contrastive learning
(1)
universal approximation
(1)
Papers
CCAHCL: Multi-Level Hypergraph Contrastive Learning for Connected Component Awareness
AAAI 2026
JurisBench: A Deep Benchmark for Assessing Large Language Models in Professional Legal Practice
ACL 2026
Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs
ICML 2025
On Designing General and Expressive Quantum Graph Neural Networks with Applications to MILP Instance Representation
ICLR 2025
Certified Machine Unlearning via Noisy Stochastic Gradient Descent
NeurIPS 2024
Efficient Algorithms for Sum-Of-Minimum Optimization
ICML 2024
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning
NeurIPS 2024
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input
NeurIPS 2024
Rethinking the Capacity of Graph Neural Networks for Branching Strategy
NeurIPS 2024
HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent
AISTATS 2023
On Representing Linear Programs by Graph Neural Networks
ICLR 2023
On Representing Mixed-Integer Linear Programs by Graph Neural Networks
ICLR 2023
On the Representation of Solutions to Elliptic PDEs in Barron Spaces
NeurIPS 2021