Su-in Lee
23 papers · 2006–2025 · 6 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
Jump to papers ↓+11 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (37) π Academic Marathon Β· Full π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
π±
Topic Pioneer
π¬
Deep Specialist
(11)
π
Triple Crown
π
Keyword Champion
(3)
π§
Keyword Pioneer
π
Trend Setter
β‘
Prolific Year Β· Productive
ποΈ
Keyword Collector
(98)
π₯
Unstoppable Β· Bronze
π
Century Club Β· Bronze
π
Conference Pioneer
Top co-authors
Research topics
Machine Learning
(20)
Core Methods
(16)
Optimization & Theory
(10)
Artificial Intelligence
(9)
Core AI
(8)
Deep Learning
(6)
Application Areas
(6)
Mathematics & Optimization
(5)
Learning Types
(5)
Mathematics
(3)
Optimization
(3)
Healthcare & Medicine
(2)
Architectures
(2)
Bayesian & Probabilistic
(2)
Models
(2)
Keywords
feature attribution
(7)
model explanation
(5)
shapley value
(5)
convex optimization
(4)
gaussian graphical model
(4)
network estimation
(3)
contrastive learning
(3)
information theory
(3)
representation learning
(2)
alternating direction method of multiplier
(2)
dynamic feature selection
(2)
latent variable
(2)
graphical model
(2)
gene expression
(2)
model interpretability
(2)
mutual information
(2)
graphical lasso
(2)
high-dimensional estimation
(2)
feature importance
(1)
vision transformer
(1)
Papers
An Efficient Framework for Crediting Data Contributors of Diffusion Models
ICLR 2025
Estimating Conditional Mutual Information for Dynamic Feature Selection
ICLR 2024
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution
NeurIPS 2024
Contrastive Corpus Attribution for Explaining Representations
ICLR 2023
Feature Selection in the Contrastive Analysis Setting
NeurIPS 2023
Learning to Estimate Shapley Values with Vision Transformers
ICLR 2023
Learning to Maximize Mutual Information for Dynamic Feature Selection
ICML 2023
On the Robustness of Removal-Based Feature Attributions
NeurIPS 2023
FastSHAP: Real-Time Shapley Value Estimation
ICLR 2022
Moment Matching Deep Contrastive Latent Variable Models
AISTATS 2022
Explaining by Removing: A Unified Framework for Model Explanation
JMLR 2021
Explaining Explanations: Axiomatic Feature Interactions for Deep Networks
JMLR 2021
Improving KernelSHAP: Practical Shapley Value Estimation Using Linear Regression
AISTATS 2021
Learning Deep Attribution Priors Based On Prior Knowledge
NeurIPS 2020
Understanding Global Feature Contributions With Additive Importance Measures
NeurIPS 2020
A Unified Approach to Interpreting Model Predictions
NeurIPS 2017
Learning Sparse Gaussian Graphical Models with Overlapping Blocks
NeurIPS 2016
UW-CSE at SemEval-2016 Task 10: Detecting Multiword Expressions and Supersenses using Double-Chained Conditional Random Fields
SemEval 2016
Efficient Dimensionality Reduction for High-Dimensional Network Estimation
ICML 2014
Learning Graphical Models With Hubs
JMLR 2014
Node-Based Learning of Multiple Gaussian Graphical Models
JMLR 2014
Structured Learning of Gaussian Graphical Models
NeurIPS 2012
Efficient Structure Learning of Markov Networks using L_1-Regularization
NeurIPS 2006