Yung-Kyun Noh

Orcid: 0000-0002-6372-9267

According to our database1, Yung-Kyun Noh authored at least 38 papers between 2008 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
DeepFold: enhancing protein structure prediction through optimized loss functions, improved template features, and re-optimized energy function.
Bioinform., December, 2023

Generalized Contrastive Divergence: Joint Training of Energy-Based Model and Diffusion Model through Inverse Reinforcement Learning.
CoRR, 2023

Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Variational Weighting for Kernel Density Ratios.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Synchronization-Aware NAS for an Efficient Collaborative Inference on Mobile Platforms.
Proceedings of the 24th ACM SIGPLAN/SIGBED International Conference on Languages, 2023

Geometrically regularized autoencoders for non-Euclidean data.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Nearest Neighbor Density Functional Estimation From Inverse Laplace Transform.
IEEE Trans. Inf. Theory, 2022

Evaluating Out-of-Distribution Detectors Through Adversarial Generation of Outliers.
CoRR, 2022

Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Reparametrization-Invariant Sharpness Measure Based on Information Geometry.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Ranked k-Spectrum Kernel for Comparative and Evolutionary Comparison of Exons, Introns, and CpG Islands.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Learning to increase matching efficiency in identifying additional b-jets in the tt̅b̅ process.
CoRR, 2021

A Riemannian geometric framework for manifold learning of non-Euclidean data.
Adv. Data Anal. Classif., 2021

Autoencoding Under Normalization Constraints.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Efficient neural network compression via transfer learning for machine vision inspection.
Neurocomputing, 2020

2019
Foreword: special issue for the journal track of the 10th Asian Conference on Machine Learning (ACML 2018).
Mach. Learn., 2019

A Machine Learning-Based Approach for the Prediction of Acute Coronary Syndrome Requiring Revascularization.
J. Medical Syst., 2019

Malware classification for identifying author groups: a graph-based approach.
Proceedings of the Conference on Research in Adaptive and Convergent Systems, 2019

2018
Generative Local Metric Learning for Nearest Neighbor Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence.
Neural Comput., 2018

K-Beam Subgradient Descent for Minimax Optimization.
CoRR, 2018

Nearest neighbor density functional estimation based on inverse Laplace transform.
CoRR, 2018

K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Generative Local Metric Learning for Kernel Regression.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Transfer learning for automated optical inspection.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Motion planning with movement primitives for cooperative aerial transportation in obstacle environment.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

2016
Direct Density Derivative Estimation.
Neural Comput., 2016

2015
Molecular learning with DNA kernel machines.
Biosyst., 2015

Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Reward Shaping for Model-Based Bayesian Reinforcement Learning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Feature selection for brain-computer interface using nearest neighbor information.
Proceedings of the 2014 International Winter Workshop on Brain-Computer Interface, 2014

2013
k-Nearest Neighbor Classification Algorithm for Multiple Choice Sequential Sampling.
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

2012
Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Learning Discriminative Metrics via Generative Models and Kernel Learning
CoRR, 2011

2010
Fluid Dynamics Models for Low Rank Discriminant Analysis.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

2008
An evolutionary Monte Carlo algorithm for predicting DNA hybridization.
Biosyst., 2008

Regularized discriminant analysis for transformation-invariant object recognition.
Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008


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