Yongchan Kwon
16 papers · 2020–2025 · 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
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(5)
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Research topics
Machine Learning
(15)
Optimization & Theory
(11)
Artificial Intelligence
(8)
Core AI
(8)
Application Areas
(7)
Core Methods
(5)
Learning Types
(3)
Deep Learning
(2)
Computer Vision
(1)
Data Science & Analytics
(1)
Mathematics & Optimization
(1)
Natural Language Processing
(1)
Analysis
(1)
Applications
(1)
Architectures
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Keywords
data valuation
(5)
shapley value
(4)
influence function
(4)
data shapley
(2)
anomaly detection
(2)
data attribution
(2)
mislabeled data detection
(2)
reinforcement learning from human feedback
(1)
binary classification
(1)
contrastive learning
(1)
feature attribution
(1)
subpopulation shift
(1)
machine unlearning
(1)
multimodal learning
(1)
data poisoning
(1)
linear regression
(1)
machine learning
(1)
density estimation
(1)
reconstruction error
(1)
time series
(1)
Papers
Certified Machine Unlearning Under High Dimensional Regime
JMLR 2025
TimeInf: Time Series Data Contribution via Influence Functions
ICLR 2025
Understanding Impact of Human Feedback via Influence Functions
ACL 2025
2D-OOB: Attributing Data Contribution Through Joint Valuation Framework
NeurIPS 2024
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models
ICLR 2024
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits
ICML 2024
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations
ICML 2023
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value
ICML 2023
OpenDataVal: a Unified Benchmark for Data Valuation
NeurIPS 2023
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning
AISTATS 2022
Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning
NeurIPS 2022
WeightedSHAP: analyzing and improving Shapley based feature attributions
NeurIPS 2022
Competing AI: How does competition feedback affect machine learning?
AISTATS 2021
Efficient Computation and Analysis of Distributional Shapley Values
AISTATS 2021
Lipschitz Continuous Autoencoders in Application to Anomaly Detection
AISTATS 2020
Principled learning method for Wasserstein distributionally robust optimization with local perturbations
ICML 2020