Trust-region learning for ICA. - Heeyoul Choi; Sookjeong Kim; Seungjin Choi (IJCNN, 2004)

Relative trust region learning for ICA. - Heeyoul Choi; Seungjin Choi (ICASSP (5), 2005)

Relative Gradient Learning for Independent Subspace Analysis. - Heeyoul Choi; Seungjin Choi (IJCNN, 2006)

A relative trust-region algorithm for independent component analysis. - Heeyoul Choi; Seungjin Choi (Neurocomputing, 2007)

Robust kernel Isomap. - Heeyoul Choi; Seungjin Choi (Pattern Recognit., 2007)

Manifold Integration with Markov Random Walks. - Heeyoul Choi; Seungjin Choi; Yoonsuck Choe (AAAI, 2008)

Sketch Recognition Based on Manifold Learning. - Heeyoul Choi; Tracy Hammond (AAAI, 2008)

Kernel oriented discriminant analysis for speaker-independent phoneme spaces. - Heeyoul Choi; Ricardo Gutierrez-Osuna; Seungjin Choi; Yoonsuck Choe (ICPR, 2008)

Gesture Recognition Based on Manifold Learning. - Heeyoul Choi; Brandon Paulson; Tracy Hammond (SSPR/SPR, 2008)

Probabilistic Combination of Multiple Evidence. - Heeyoul Choi; Anup Katake; Seungjin Choi; Yoonseop Kang; Yoonsuck Choe (ICONIP (1), 2009)

Fast and accurate retinal vasculature tracing and kernel-Isomap-based feature selection. - Donghyeop Han; Heeyoul Choi; Choonseog Park; Yoonsuck Choe (IJCNN, 2009)

Self-Organization of Tactile Receptive Fields: Exploring Their Textural Origin and Their Representational Properties. - Choonseog Park; Heeyoul Choi; Yoonsuck Choe (WSOM, 2009)

Learning alpha-integration with partially-labeled data. - Heeyoul Choi; Seungjin Choi; Anup Katake; Yoonsuck Choe (ICASSP, 2010)

Alpha-integration of multiple evidence. - Heeyoul Choi; Anup Katake; Seungjin Choi; Yoonsuck Choe (ICASSP, 2010)

Manifold Alpha-Integration. - Heeyoul Choi; Seungjin Choi; Anup Katake; Yoonseop Kang; Yoonsuck Choe (PRICAI, 2010)

From Data Streams to Information Flow: Information Exchange in Child-Parent Interaction. - Heeyoul Choi; Chen Yu 001; Linda B. Smith; Olaf Sporns (CogSci, 2011)

Dynamic learning for visual representation of asymmetric proximity. - Heeyoul Choi (SMC, 2012)

Sound-based real-time context recognition on smartphone. - Heeyoul Choi; Sunjae Lee; Jaemo Sung; Sangdo Park (ICCE, 2013)

Parameter Learning for Alpha Integration. - Heeyoul Choi; Seungjin Choi; Yoonsuck Choe (Neural Comput., 2013)

Data visualization for asymmetric relations. - Heeyoul Choi (Neurocomputing, 2014)

Localization and regularization of normalized transfer entropy. - Heeyoul Choi (Neurocomputing, 2014)

RNNDROP: A novel dropout for RNNS in ASR. - Taesup Moon; Heeyoul Choi; Hoshik Lee; Inchul Song (ASRU, 2015)

A Neural Knowledge Language Model. - Sungjin Ahn; Heeyoul Choi; Tanel Pärnamaa; Yoshua Bengio (CoRR, 2016)

Context-dependent word representation for neural machine translation. - Heeyoul Choi; Kyunghyun Cho; Yoshua Bengio (Comput. Speech Lang., 2017)

Fast Depthwise Separable Convolution for Embedded Systems. - Byeongheon Yoo; Yongjun Choi; Heeyoul Choi (ICONIP (7), 2018)

Gradient Acceleration in Activation Functions. - Sangchul Hahn; Heeyoul Choi (CoRR, 2018)

Alpha-Pooling for Convolutional Neural Networks. - Hayoung Eom; Heeyoul Choi (CoRR, 2018)

Disentangling Latent Factors with Whitening. - Sangchul Hahn; Heeyoul Choi (CoRR, 2018)

Fine-grained attention mechanism for neural machine translation. - Heeyoul Choi; Kyunghyun Cho; Yoshua Bengio (Neurocomputing, 2018)

Machine Learning-based Prediction of VNF Deployment Decisions in Dynamic Networks. - Stanislav Lange; Heegon Kim; Seyeon Jeong; Heeyoul Choi; Jae-Hyoung Yoo; James Won-Ki Hong (APNOMS, 2019)

Predicting VNF Deployment Decisions under Dynamically Changing Network Conditions. - Stanislav Lange; Heegon Kim; Seyeon Jeong; Heeyoul Choi; Jae-Hyoung Yoo; James Won-Ki Hong (CNSM, 2019)

Disentangling Latent Factors of Variational Auto-encoder with Whitening. - Sangchul Hahn; Heeyoul Choi (ICANN (3), 2019)

A Deep Learning Approach to VNF Resource Prediction using Correlation between VNFs. - Heegon Kim; Seyeon Jeong; Doyoung Lee; Heeyoul Choi; Jae-Hyoung Yoo; James Won-Ki Hong (NetSoft, 2019)

Machine Learning-Based Method for Prediction of Virtual Network Function Resource Demands. - Heegon Kim; Doyoung Lee; Seyeon Jeong; Heeyoul Choi; Jae-Hyoung Yoo; James Won-Ki Hong (NetSoft, 2019)

Self-Knowledge Distillation in Natural Language Processing. - Sangchul Hahn; Heeyoul Choi (RANLP, 2019)

Network Intrusion Detection based on LSTM and Feature Embedding. - Hyeokmin Gwon; Chungjun Lee; Rakun Keum; Heeyoul Choi (CoRR, 2019)

Active Search for Nearest Neighbors. - Hayoung Um; Heeyoul Choi (CoRR, 2019)

Persistent hidden states and nonlinear transformation for long short-term memory. - Heeyoul Choi (Neurocomputing, 2019)

Graph Neural Network based Service Function Chaining for Automatic Network Control. - DongNyeong Heo; Stanislav Lange; Heegon Kim; Heeyoul Choi (APNOMS, 2020)

Graph Neural Network-based Virtual Network Function Management. - Heegon Kim; Suhyun Park; Stanislav Lange; Doyoung Lee; DongNyeong Heo; Heeyoul Choi; Jae-Hyoung Yoo; James Won-Ki Hong (APNOMS, 2020)

Graph Neural Network-based Virtual Network Function Deployment Prediction. - Heegon Kim; Suhyun Park; DongNyeong Heo; Stanislav Lange; Heeyoul Choi; Jae-Hyoung Yoo; James Won-Ki Hong (CNSM, 2020)

Reinforcement Learning of Graph Neural Networks for Service Function Chaining. - DongNyeong Heo; Doyoung Lee; Heegon Kim; Suhyun Park; Heeyoul Choi (CoRR, 2020)

Understanding dropout as an optimization trick. - Sangchul Hahn; Heeyoul Choi (Neurocomputing, 2020)

Sequential Deep Learning Architectures for Anomaly Detection in Virtual Network Function Chains. - Chungjun Lee; Jibum Hong; DongNyeong Heo; Heeyoul Choi (ICTC, 2021)

Deep Neural Networks and End-to-End Learning for Audio Compression. - Daniela N. Rim; Inseon Jang; Heeyoul Choi (CoRR, 2021)

Adversarial Training with Contrastive Learning in NLP. - Daniela N. Rim; DongNyeong Heo; Heeyoul Choi (CoRR, 2021)

Systematic Review for AI-based Language Learning Tools. - Jin Ha Woo; Heeyoul Choi (CoRR, 2021)

Graph neural network-based virtual network function deployment optimization. - Heegon Kim; Suhyun Park; Stanislav Lange; Doyoung Lee; DongNyeong Heo; Heeyoul Choi; Jae-Hyoung Yoo; James Won-Ki Hong (Int. J. Netw. Manag., 2021)

Reinforcement Learning of Graph Neural Networks for Service Function Chaining in Computer Network Management. - DongNyeong Heo; Doyoung Lee; Heegon Kim; Suhyun Park; Heeyoul Choi (APNOMS, 2022)

Updating VNF deployment with Scaling Actions using Reinforcement Algorithms. - Namjin Seo; DongNyeong Heo; Jibum Hong; Heegon Kim; Jae-Hyoung Yoo; James Won-Ki Hong; Heeyoul Choi (APNOMS, 2022)

Partitioning Image Representation in Contrastive Learning. - Hyunsub Lee; Heeyoul Choi (ICPR, 2022)

End-to-End Training of Both Translation Models in the Back-Translation Framework. - DongNyeong Heo; Heeyoul Choi (CoRR, 2022)

Enhanced Labeling Technique for Reddit Text and Fine-Tuned Longformer Models for Classifying Depression Severity in English and Luganda. - Richard Kimera; Daniela N. Rim; Joseph Kirabira; Ubong Godwin Udomah; Heeyoul Choi (ICTC, 2023)

Fine-Tuning BERT on Twitter and Reddit Data in Luganda and English. - Richard Kimera; Daniela N. Rim; Heeyoul Choi (NLPIR, 2023)

Graph Attention Multi-Agent Fleet Autonomy for Advanced Air Mobility. - Malintha Fernando; Ransalu Senanayake; Heeyoul Choi; Martin Swany (Robotics: Science and Systems, 2023)

Building a Parallel Corpus and Training Translation Models Between Luganda and English. - Richard Kimera; Daniela N. Rim; Heeyoul Choi (CoRR, 2023)

Advanced Scaling Methods for VNF deployment with Reinforcement Learning. - Namjin Seo; DongNyeong Heo; Heeyoul Choi (CoRR, 2023)

Shared Latent Space by Both Languages in Non-Autoregressive Neural Machine Translation. - DongNyeong Heo; Heeyoul Choi (CoRR, 2023)

Fast Training of NMT Model with Data Sorting. - Daniela N. Rim; Richard Kimera; Heeyoul Choi (CoRR, 2023)

End-To-End Training of Back-Translation Framework with Categorical Reparameterization Trick. - DongNyeong Heo; Heeyoul Choi (ICANN (7), 2024)

Multimodal Representation Loss Between Timed Text and Audio for Regularized Speech Separation. - Tsun-An Hsieh; Heeyoul Choi; Minje Kim (INTERSPEECH, 2024)

Data Augmentation With Back translation for Low Resource languages: A case of English and Luganda. - Richard Kimera; DongNyeong Heo; Daniela N. Rim; Heeyoul Choi (NLPIR, 2024)

Convolutional Lie Operator for Sentence Classification. - Daniela Noemi Rim; Heeyoul Choi (NLPIR, 2024)

Anomaly detection based on system text logs of virtual network functions. - Daniela N. Rim; DongNyeong Heo; Chungjun Lee; Sukhyun Nam; Jae-Hyoung Yoo; James Won-Ki Hong; Heeyoul Choi (Big Data Res., 2024)

Advancing AI with Integrity: Ethical Challenges and Solutions in Neural Machine Translation. - Richard Kimera; Yun-Seon Kim; Heeyoul Choi (CoRR, 2024)

Empirical Study of Symmetrical Reasoning in Conversational Chatbots. - Daniela N. Rim; Heeyoul Choi (CoRR, 2024)

N-gram Prediction and Word Difference Representations for Language Modeling. - DongNyeong Heo; Daniela Noemi Rim; Heeyoul Choi (CoRR, 2024)

Generalized Probabilistic Attention Mechanism in Transformers. - DongNyeong Heo; Heeyoul Choi (CoRR, 2024)

Pre-trained Models for Bytecode Instructions. - Donggyu Kim; Taemin Kim; Jiho Shin; Song Wang; Heeyoul Choi; Jaechang Nam (ICST, 2025)

Harnessing EHRs for Diffusion-based Anomaly Detection on Chest X-rays. - Harim Kim; Yuhan Wang; Minkyu Ahn; Heeyoul Choi; Yuyin Zhou; Charmgil Hong (CoRR, 2025)

Dynamic Preference Multi-Objective Reinforcement Learning for Internet Network Management. - DongNyeong Heo; Daniela Noemi Rim; Heeyoul Choi (CoRR, 2025)