Dongha Kim
9 papers · 2020–2026 · 4 venues · across top CS/AI venues
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Achievements
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🌉 Interdisciplinary Bridge · Bronze 🏃 Academic Marathon · Sprint 🗺️ Taxonomy Completionist (26) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Bronze
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Unstoppable · Bronze
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Keyword Collector
(52)
Venues
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Research topics
Machine Learning
(9)
Deep Learning
(7)
Learning Types · Machine Learning
(5)
Models
(5)
Core Methods
(4)
Application Areas
(3)
Learning Types · Deep Learning
(3)
Optimization & Theory · Machine Learning
(3)
Artificial Intelligence
(2)
Architectures
(2)
Core AI
(2)
Computer Vision
(1)
Analysis
(1)
Optimization & Theory · Deep Learning
(1)
Keywords
deep generative model
(4)
outlier detection
(3)
curse of dimensionality
(2)
inlier memorization
(2)
manifold learning
(1)
anomaly detection
(1)
representation learning
(1)
data augmentation
(1)
algorithmic fairness
(1)
adversarial training
(1)
computational efficiency
(1)
em algorithm
(1)
label noise
(1)
nonparametric estimation
(1)
likelihood estimation
(1)
excess risk
(1)
density estimation
(1)
generative model
(1)
diffusion model
(1)
adversarial robustness
(1)
Papers
Memorize Early, Then Query: Inlier-Memorization-Guided Active Outlier Detection
AAAI 2026
Nonparametric Estimation of a Factorizable Density using Diffusion Models
JMLR 2026
ALTBI: Constructing Improved Outlier Detection Models via Optimization of Inlier-Memorization Effect
AAAI 2025
IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples
AAAI 2024
ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
ICML 2024
A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models
JMLR 2023
Learning fair representation with a parametric integral probability metric
ICML 2022
Kernel-convoluted Deep Neural Networks with Data Augmentation
AAAI 2021
On casting importance weighted autoencoder to an EM algorithm to learn deep generative models
AISTATS 2020