Yung-kyun Noh
15 papers · 2010–2026 · 5 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Full π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (37)
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Century Club Β· Bronze
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(5)
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Research topics
Machine Learning
(14)
Core Methods
(11)
Optimization & Theory
(8)
Deep Learning
(5)
Learning Types
(5)
Reinforcement Learning
(3)
Methods
(3)
Computer Vision
(2)
Mathematics & Optimization
(2)
Analysis
(2)
Architectures
(2)
Bayesian & Probabilistic
(2)
Models
(2)
Artificial Intelligence
(1)
Interdisciplinary
(1)
Keywords
metric learning
(4)
energy-based model
(3)
nearest neighbor
(2)
generative model
(2)
off-policy evaluation
(2)
importance sampling
(2)
nonparametric estimation
(2)
diffusion model
(2)
bias reduction
(2)
nearest neighbor classification
(2)
feature selection
(1)
density estimation
(1)
change detection
(1)
kl divergence
(1)
adversarial learning
(1)
neural decoding
(1)
anomaly detection
(1)
outlier detection
(1)
domain adaptation
(1)
inverse reinforcement learning
(1)
Papers
On the Information Processing of One-Dimensional Wasserstein Distances with Finite Samples
AAAI 2026
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies
ICLR 2024
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
NeurIPS 2024
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach
NeurIPS 2023
Geometrically regularized autoencoders for non-Euclidean data
ICLR 2023
Variational Weighting for Kernel Density Ratios
NeurIPS 2023
A Reparametrization-Invariant Sharpness Measure Based on Information Geometry
NeurIPS 2022
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions
NeurIPS 2022
Autoencoding Under Normalization Constraints
ICML 2021
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
ICML 2018
Generative Local Metric Learning for Kernel Regression
NeurIPS 2017
Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation
AISTATS 2015
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence
AISTATS 2014
Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification
NeurIPS 2012
Generative Local Metric Learning for Nearest Neighbor Classification
NeurIPS 2010