Hyeryung Jang

Expert Syst. Appl., 2025

2024

I2AM: Interpreting Image-to-Image Latent Diffusion Models via Attribution Maps.

[BibT_eX]

[DOI]

Junseo Park

CoRR, 2024

Text-to-Image Synthesis for Any Artistic Styles: Advancements in Personalized Artistic Image Generation via Subdivision and Dual Binding.

[BibT_eX]

[DOI]

Junseo Park

Beom-Seok Ko

CoRR, 2024

Data Augmentation Techniques Using Text-to-Image Diffusion Models for Enhanced Data Diversity.

[BibT_eX]

[DOI]

Jeongmin Shin

Proceedings of the 15th International Conference on Information and Communication Technology Convergence, 2024

2023

LinkFND: Simple Framework for False Negative Detection in Recommendation Tasks With Graph Contrastive Learning.

[BibT_eX]

[DOI]

Sanghun Kim

IEEE Access, 2023

StyleBoost: A Study of Personalizing Text-to-Image Generation in Any Style using DreamBooth.

[BibT_eX]

[DOI]

Junseo Park

Beom-Seok Ko

Proceedings of the 14th International Conference on Information and Communication Technology Convergence, 2023

2022

On Cost-Efficient Learning of Data Dependency.

[BibT_eX]

[DOI]

HyungSeok Song

IEEE/ACM Trans. Netw., 2022

Multisample Online Learning for Probabilistic Spiking Neural Networks.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2022

Learning to Broadcast for Ultra-Reliable Communication With Differential Quality of Service via the Conditional Value at Risk.

[BibT_eX]

[DOI]

IEEE Trans. Commun., 2022

Bayesian continual learning via spiking neural networks.

[BibT_eX]

[DOI]

Frontiers Comput. Neurosci., 2022

2021

Learning to Demodulate From Few Pilots via Offline and Online Meta-Learning.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2021

Spiking Neural Networks - Part III: Neuromorphic Communications.

[BibT_eX]

[DOI]

IEEE Commun. Lett., 2021

Spiking Neural Networks - Part II: Detecting Spatio-Temporal Patterns.

[BibT_eX]

[DOI]

IEEE Commun. Lett., 2021

Spiking Neural Networks - Part I: Detecting Spatial Patterns.

[BibT_eX]

[DOI]

IEEE Commun. Lett., 2021

Learning to Time-Decode in Spiking Neural Networks Through the Information Bottleneck.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Multi-Sample Online Learning for Spiking Neural Networks Based on Generalized Expectation Maximization.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

BiSNN: Training Spiking Neural Networks with Binary Weights via Bayesian Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Multi-Compartment Variational Online Learning for Spiking Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

VOWEL: A Local Online Learning Rule for Recurrent Networks of Probabilistic Spiking Winner- Take-All Circuits.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

End-to-End Learning of Neuromorphic Wireless Systems for Low-Power Edge Artificial Intelligence.

[BibT_eX]

[DOI]

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Simulation-Based Distributed Coordination Maximization Over Networks.

[BibT_eX]

[DOI]

Jinwoo Shin

IEEE Trans. Control. Netw. Syst., 2019

An Introduction to Probabilistic Spiking Neural Networks: Probabilistic Models, Learning Rules, and Applications.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2019

An Introduction to Probabilistic Spiking Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Learning How to Demodulate from Few Pilots via Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2019

Solving Continual Combinatorial Selection via Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Training Dynamic Exponential Family Models with Causal and Lateral Dependencies for Generalized Neuromorphic Computing.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Game Theoretic Perspective of Optimal CSMA.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2018

Learning Data Dependency with Communication Cost.

[BibT_eX]

[DOI]

HyungSeok Song

Proceedings of the Nineteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2018

2017

Traffic Scheduling and Revenue Distribution Among Providers in the Internet: Tradeoffs and Impacts.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2017

Adiabatic Persistent Contrastive Divergence learning.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

2016

Distributed coordination maximization over networks: a stochastic approximation approach.

[BibT_eX]

[DOI]

Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2016

2014

Distributed learning for utility maximization over CSMA-based wireless multihop networks.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE Conference on Computer Communications, 2014

2013

On the interaction between content-oriented traffic scheduling and revenue sharing among providers.

[BibT_eX]

[DOI]

Proceedings of the 2013 Proceedings IEEE INFOCOM Workshops, 2013

Network traffic reduction through smart network.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Information Networking 2013, 2013

2012

On the stability of ISPs' coalition structure: Shapley value based revenue sharing.

[BibT_eX]

[DOI]

Proceedings of the 46th Annual Conference on Information Sciences and Systems, 2012

2010

On the interaction between ISP revenue sharing and network neutrality.

[BibT_eX]

[DOI]

Hyojung Lee