Wu Lin
10 papers · 2017–2024 · 4 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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πΊοΈ Taxonomy Completionist (19) π Academic Marathon Β· Sprint π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π
Keyword Champion
(2)
π
Conference Pioneer
π₯
Unstoppable Β· Bronze
β
The Questioner
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(53)
Venues
Top co-authors
Research topics
Machine Learning
(10)
Optimization & Theory Β· Machine Learning
(9)
Deep Learning
(7)
Artificial Intelligence
(2)
Application Areas
(2)
Bayesian & Probabilistic Β· Machine Learning
(2)
Core Methods
(2)
Models
(2)
Optimization & Theory Β· Deep Learning
(2)
Techniques
(2)
Mathematics & Optimization
(1)
Architectures
(1)
Bayesian & Probabilistic Β· Artificial Intelligence
(1)
Core AI
(1)
Learning Types
(1)
Keywords
variational inference
(6)
natural gradient
(4)
deep learning
(2)
natural gradient descent
(2)
second-order optimization
(2)
model behavior
(1)
uncertainty quantification
(1)
stochastic gradient descent
(1)
gradient-based method
(1)
fisher information matrix
(1)
exponential family
(1)
matrix optimization
(1)
weight perturbation
(1)
bayesian inference
(1)
stochastic process
(1)
variational message passing
(1)
mean-field approximation
(1)
mirror descent
(1)
data valuation
(1)
stochastic gradient
(1)
Papers
Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective
ICML 2024
Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC
ICML 2024
Training Data Attribution via Approximate Unrolling
NeurIPS 2024
Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning
ICML 2023
Tractable structured natural-gradient descent using local parameterizations
ICML 2021
Handling the Positive-Definite Constraint in the Bayesian Learning Rule
ICML 2020
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations
ICML 2019
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
ICML 2018
Variational Message Passing with Structured Inference Networks
ICLR 2018
Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models
AISTATS 2017