Emmanuel Abbe
27 papers · 2015–2025 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (42) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
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Deep Specialist
(18)
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Triple Crown
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Topic Evolution
π
Keyword Champion
(3)
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Prolific Year Β· Productive
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Trend Setter
ποΈ
Keyword Collector
(110)
β
The Questioner
(2)
π₯
Unstoppable Β· Bronze
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Renaissance Researcher
(5)
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Century Club Β· Bronze
Venues
Top co-authors
Research topics
Machine Learning
(25)
Optimization & Theory Β· Machine Learning
(23)
Deep Learning
(14)
Architectures
(12)
Optimization & Theory Β· Deep Learning
(9)
Mathematics & Optimization
(7)
Mathematics
(7)
Core Methods
(6)
Artificial Intelligence
(5)
Core AI
(4)
Computer Science
(3)
Foundations
(3)
Learning Types Β· Deep Learning
(3)
Learning Types Β· Machine Learning
(3)
Optimization
(3)
Keywords
neural network
(10)
gradient descent
(8)
learning theory
(6)
stochastic gradient descent
(5)
stochastic block model
(4)
community detection
(4)
out-of-distribution generalization
(4)
curriculum learning
(3)
belief propagation
(3)
boolean function
(3)
influence maximization
(2)
generalization error
(2)
generalization bound
(2)
sample complexity
(2)
deep learning
(2)
network analysis
(2)
graph clustering
(2)
differentiable learning
(2)
neural network optimization
(2)
information theory
(2)
Papers
Learning High-Degree Parities: The Crucial Role of the Initialization
ICLR 2025
Generalization on the Unseen, Logic Reasoning and Degree Curriculum
JMLR 2024
How Far Can Transformers Reason? The Globality Barrier and Inductive Scratchpad
NeurIPS 2024
On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions
ICML 2024
Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization
NeurIPS 2024
When can transformers reason with abstract symbols?
ICLR 2024
Generalization on the Unseen, Logic Reasoning and Degree Curriculum
ICML 2023
Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs
NeurIPS 2023
SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics
COLT 2023
Transformers learn through gradual rank increase
NeurIPS 2023
An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to Learn
ICML 2022
Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures
NeurIPS 2022
On the non-universality of deep learning: quantifying the cost of symmetry
NeurIPS 2022
The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks
COLT 2022
On the Power of Differentiable Learning versus PAC and SQ Learning
NeurIPS 2021
Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels
ICML 2021
Stochastic block model entropy and broadcasting on trees with survey
COLT 2021
The staircase property: How hierarchical structure can guide deep learning
NeurIPS 2021
Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Networks
JMLR 2020
Generalized Nonbacktracking Bounds on the Influence
JMLR 2020
On the universality of deep learning
NeurIPS 2020
Chaining Mutual Information and Tightening Generalization Bounds
NeurIPS 2018
Communication-Computation Efficient Gradient Coding
ICML 2018
Community Detection and Stochastic Block Models: Recent Developments
JMLR 2018
Nonbacktracking Bounds on the Influence in Independent Cascade Models
NeurIPS 2017
Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation
NeurIPS 2016
Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters
NeurIPS 2015