Morgane Austern
7 papers · 2019–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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Conference Polyglot · Silver
🏃
Academic Marathon · Sprint
🌉
Interdisciplinary Bridge · Bronze
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Taxonomy Completionist
(16)
Top co-authors
Research topics
Machine Learning
(7)
Optimization & Theory
(7)
Deep Learning
(3)
Core Methods
(2)
Learning Types · Machine Learning
(2)
Artificial Intelligence
(1)
Computer Science
(1)
Mathematics & Optimization
(1)
Architectures
(1)
Core AI
(1)
Foundations
(1)
Learning Types · Deep Learning
(1)
Mathematics
(1)
Techniques
(1)
Keywords
node classification
(2)
model compression
(1)
causal inference
(1)
image classification
(1)
stochastic gradient descent
(1)
link prediction
(1)
model selection
(1)
logistic regression
(1)
graph matching
(1)
data augmentation
(1)
graph representation
(1)
empirical risk minimization
(1)
asymptotic analysis
(1)
asymptotic risk
(1)
generalization bound
(1)
asymptotic normality
(1)
confidence interval
(1)
asymptotic distribution
(1)
network embedding
(1)
sample splitting
(1)
Papers
Perfect Recovery for Random Geometric Graph Matching with Shallow Graph Neural Networks
AISTATS 2025
Universality of High-Dimensional Logistic Regression and a Novel CGMT under Dependence with Applications to Data Augmentation
COLT 2025
Asymptotics of Network Embeddings Learned via Subsampling
JMLR 2023
Debiased Machine Learning without Sample-Splitting for Stable Estimators
NeurIPS 2022
Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection
NeurIPS 2021
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data
AISTATS 2019
Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach
ICLR 2019