1. Kim, D., Jung, G. and Yang, J. (2025.12). Enhancing Coreference Resolution with LLM-driven Data Augmentation and Adversarial Filtering. Proceedings of the 14th International Joint Conference on Natural Language Processing & Asia-Pacific Chapter of the Association for Computational Linguistics Findings(IJCNLP-AACL Findings), Mumbai, India.
  2. Oh, J., Choe, S. & Yang, J. (2025.12). QNQCDE: Efficient Dialogue Embeddings based on Contrastive Learning using Questions and Non-Question Pairs. Proceedings of the 13th IEEE International Conference on Big Data (BigData), Macau, China.
  3. Choe, S., Oh, J. & Yang, J. (2025.6). Multimodal Contrastive Learning for Dialogue Embeddings with Global and Local Views. Proceedings of the 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Sydney, Australia.
  4. Kim, D., Kim, T. and Yang, J. (2025.4). Early Detection of Online Grooming with Language Models. Proceedings of the 40th ACM/SIGAPP Symposium On Applied Computing (SAC), Catania, Italy.
  5. Choi, H., Na, C., Oh, J., Lee, S., Kim, J., Choe, S., Lee, J., Kim, T. and Yang, J. (2024. 6). Reciprocal Attention Mixing Transformer for Lightweight Image Restoration. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshop - NTIRE (CVPRW), Seattle, USA. (arXiv)
  6. Hwang, J., Bang, S., Choi, M., Hong, S., Kim, S., Lee, H., Yang, J., Park, U. & Choi, Y. (2024.5). Discovery and Validation of Survival-Specific Genes in Papillary Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel . Cancers, 16(11).
  7. Seo, K., Lee, S., Cho, W., Song, Y. & Yang, J. (2024.5). Multi-Time Window Ensemble and Maximization of Expected Return for Stock Movement Prediction. Proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Taipei, Taiwan.
  8. Seo, K. and Yang, J. (2024.4). Exploring The Efficient Market Hypothesis for Accurate Stock Movement Prediction via Feature-Axis Transformer. Proceedings of the 39th ACM/SIGAPP Symposium On Applied Computing (SAC), Avila, Spain.
  9. Choi, H., Na, C., Kim J. and Yang, J. (2023. 6). Exploration of Lightweight Single Image Denoising with Transformers and Truly Fair Training. Proceedings of the 2023 International Conference on Multimedia Retrieval (ICMR), Thessaloniki, Greece. (arXiv)
  10. Choi, H., Lee, J. and Yang, J. (2023. 6). N-Gram in Swin Transformers for Efficient Lightweight Image Super-Resolution. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada. (arXiv)
  11. Seo, K. and Yang, J. (2023.3). Exploring Candlesticks and Multi-Time Windows for Forecasting Stock-Index Movements. Proceedings of the 38th ACM/SIGAPP Symposium On Applied Computing (SAC), Tallinn, Estonia.
  12. Seo, K. and Yang, J. (2022.12). Exploring Multi-Time Context Vector and Randomness for Stock Movement Prediction. Proceedings of the IEEE International Conference on Big Data (Big Data), Osaka, Japan, pp. 1114-1123, doi: 10.1109/BigData55660.2022.10020373.
  13. Hwang, J., Kim, H, Han, J., Lee, J., Hong, S., Kim, S., Kim, S., Choi, K., Yang, J., Park, U., Kim, K., Yim, K. & Choi, Y. (2022.1). Identification of Survival-Specific Genes in Clear Cell Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel . Journal of Personalized Medicine, 12(1).
  14. Seo, K., Chung, B., Panchaseelan, HP., Kim, T., Park, H., Oh, B., Chun, M., Won, S., Kim, D., Beom, J., Jeon, D. & Yang, J. (2021. 6). Forecasting the Walking Assistance Rehabilitation Level of Stroke Patients Using Artificial Intelligence. Diagnostics, 11(6), 1096.  
  15. Seo, K. and Yang, J. (2020. 9). Differentially Private Actor and Its Eligibility Trace. Electronics, 9(9), 1486.
  16. Kim, T. and Yang, J. (2020. 6). Selective Feature Anonymization for Privacy-Preserving Image Data Publishing. Electronics, 9(5), 874.
  17. Chung, D., Zhang, K. & Yang, J. (2019. 8). Method for Identifying Cancer-Related Genes Using Gene Similarity-Based Collaborative Filtering. Journal of Computational Biology 26(8):875-881.
  18. Kim, T. and Yang, J. (2019. 6). Latent-Space-Level Image Anonymization with Adversarial Protector Networks. IEEE Access 7: 84992-84999.
  19. Ahn, J., Shin, D., Kim, K. & Yang, J. (2017. 10). Indoor Air Quality Analysis Using Deep Learning with Sensor Data. Sensors 17(11). 
  20. Lee, J., Oh, B., Yang, J. & Park, U. (2017. 9). RLCF A Collaborative Filtering Approach Based on Reinforcement Learning With Sequential Ratings. Intelligent Automation & Soft Computing 23(3): 439-444.
  21. Oh, B. and Yang, J. (2016. 12). Enhancing Label Inference Algorithms Considering Vertex Importance in Graph-Based Semi-Supervised Learning. Proceedings of the International Conference on Pattern Recognition (ICPR'16). Cancun, Mexico.
  22. Oh, B., Yu, J., Yang, J., Nang, J. and Park, S. (2013. 10). Fast and Accurate Home Photo Categorization for Handheld Devices using MPEG-7 Descriptors. International Journal of Computers, Communication and Control 8(5): 722-735.
  23. Lee, B., Choi, S., Oh, B., Yang, J. and Park, S. (2013. 8). A New Ensemble Learning Algorithm using Regional Classifiers. International Journal on Artificial Intelligence Tools 22(4).
  24. Lee, J. and Yang, J. (2012.9). DGA: A Fast and Scalable Re-routing Algorithm based on Shortest Path and Genetic Algorithms. International Journal of Computers, Communications and Control 7(3): 482-493.
  25. Lee, J., Oh, B., Yang, J. and Park, S. (2012. 7). A Reinforcement Learning Approach for Collaborative Filtering. Proceedings of the Second International Conference on Computers, Networks, Systems, and Industrial Applications (CNSI'12). Jeju, Korea. pp. 194-199.
  26. Yun, C., Oh, B., Yang, J. and Nang, J. (2011.9). Feature Subset Selection Based on Bio-Inspired Algorithms. Journal of information Science and Engineering 27(5): 1667-1686.
  27. Oh, B., Na, Y., Yang, J., Park, S., Nang, J. and Kim, J. (2010.11). Genetic Algorithm-based Dynamic Vehicle Route Search using Car-to-Car Communication. Advances in Electrical and Computer Engineering 10(4): 81-86.
  28. Na, Y. and Yang, J. (2010. 7). Distributed Bayesian Network Structure Learning. Proceedings of the IEEE International Symposium on Industrial Electronics (ISIE'10). Bari, Itary.
  29. Nang, J., Park, J., Yang, J. and Kim, S. (2010. 3). A Hierarchical Bitmap Indexing Method for Similarity Search in High-Dimensional Multimedia Databases. Journal of information Science and Engineering 26(2): 393-407.
  30. Kim, S., Yoon, J., Yang, J. and Park, S. (2010. 2).Walk-Weighted Subsequence Kernels for Protein-Protein Interaction Extraction. BMC Bioinformatics 11(107).
  31. Lee, H., Oh, B., Yang, J. and Kim, S. (2009.05). Distributed Genetic Algorithm using Automatic Migration Control. Proceedings of the Eleventh IEEE Congress on Evolutionary Computation (CEC'09). Trondheim, Norway.
  32. Lee, B., Na, Y., Oh, B. and Yang, J. (2008.11). Ensemble Learning of Regional Classifiers. Proceedings of the Twentieth IEEE International Conference on Tools with Artificial Intelligence (ICTAI'08). Dayton Ohio, USA. pp. 387-392.
  33. Jo, H., Na, Y., Oh, B. and Yang, J. (2008.11). Attribute Value Taxonomy Generation through Matrix Based Adaptive Genetic Algorithm. Proceedings of the Twentieth IEEE International Conference on Tools with Artificial Intelligence (ICTAI'08). Dayton Ohio, USA. pp. 393-400.
  34. Yang, J. (2008.1). Book Review: Bioinformatics-FromGenomes to Therapies. Briefings in Bioinformatics 9(1): 91-93.
  35. Kim, S., Yoon, J. and Yang, J. (2008. 1). Kernel Approaches for Genic Interaction Extraction. Bioinformatics 24(1).
  36. Yun, C. and Yang, J. (2007.10). Experimental Comparison of Feature Subset Selection Methods. Proceedings of the Seventh IEEE International Conference on Data Mining (ICDM'07). Omaha NE, USA. (accepted for workshop)
  37. Choi, S., Lee, B. and Yang, J. (2007.10). Ensembles of Region Based Classifiers. Proceedings of the Seventh International Conference on Computer and Information Technology (CIT'07). University of Aizu, Fukushima Japan. pp. 41-46. (Best Paper Award)
  38. Yun, C., Shin, D., Yang, J. and Kim, S. (2007. 10). An Experimental Study on Feature Subset Selection Methods. Proceedings of the Seventh International Conference on Computer and Information Technology (CIT'07). University of Aizu, Fukushima Japan. pp. 77-82
  39. Kang, S., Lee, B., Yang, J., Kim, S. and Kim, S. (2007.10). Simulating Biological Pathways with a Continuous Petri Net Using Runge-Kutta Methods. Frontiers in the Convergence of Bioscience and Information Technologies (FBIT'07). Jeju-Do, Korea.
  40. Yang, J., Choi, Y., Hong, K., Park, J. and Kim, S. (2007.10). Automated Classification and Information Extraction of Biological Text. Frontiers in the Convergence of Bioscience and Information Technologies (FBIT'07). Jeju-Do, Korea.
  41. Jo, H., Lee, B., Na, Y., Lee, H., Oh, B., Yun, C., Yang, J., Lee, M. and Kim, M. (2007.10). Prioritized Traffic Information Delivery Based on Historical Data Analysis. Proceedings of the Tenth IEEE Intelligent Transportation Systems Conference (ITSC'07). Seattle, Wa, USA. pp. 568-573.
  42. Lee, K., Joo, J., Yang, J. and Honavar, V. (2006.8). Experimental Comparison of Feature Subset Selection Using GA and ACO Algorithm. Proceedings of the Second International Conference on Advanced Data Mining and Applications (ADMA'06). Xi'an, China. pp. 465-472. (LNAI 4093)
  43. Lee, S., Yang, J. and Park., S. (2006.8). A New Polynimial Time Algorithm for Bayesian Network Structure Learning. Proceedings of the Second International Conference on Advanced Data Mining and Applications (ADMA'06). Xi'an, China. pp. 501-508. (LNAI 4093)
  44. Hong, K., Park, J., Yang, J. and Park, S. (2005.12). Biological Text Mining for Extraction of Proteins and Their Interactions. Proceedings of the First International Conference on Pattern Recognition and Machine Intelligence (PReMI'05). Kolkata, Indida. pp. 645-648. (LNCS 3776)
  45. Jang, J., Han, S., Park, S. and Yang, J. (2005.11). A Content-Based Load Balancing Algorithm for Metadata Servers in Cluster File Systems. Proceedings of the Third International Symposium on Parallel and Distributed Processing and Applications (ISPA'05). Nanjing, China. pp. 49-57. (LNCS 3758)
  46. Hong, K., Park, J., Yang, J. and Paek, E. (2005.10). Automatic Extraction of Proteins and Their Interactions from Biological Text. Proceedings of the Eighth International Conference on Discovery Science (DS'05). Singapore. pp. 322-329. (LNAI 3735)
  47. Lee, K., Joo, J., Yang, J. and Park, S. (2005.10). Unit Volume Based Distributed Clustering Using Probabilistic Mixture Model. Proceedings of the Eighth International Conference on Discovery Science (DS'05). Singapore. pp. 338-345. (LNAI 3735)
  48. Song, J., Park, S. and Yang, J. (2004.12). An Adaptive Proximity Route Selection Scheme in DHT-Based Peer to Peer Systems. Proceedings of the Fifth International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT'04). Singapore. pp. 778-781. (LNCS 3320)
  49. Joo, J., Zhang, J., Yang, J. and Honavar, V. (2004.10). Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data. Proceedings of the Seventh International Conference on Discovery Science (DS'04). Padova, Italy. pp. 347-354. (LNAI 3245)
  50. Lee, S., Yang, J. and Park, S. (2004.10). Discovery of Hidden Similarity on Collaborative Filtering to Overcome Sparsity Problem. Proceedings of the Seventh International Conference on Discovery Science (DS'04). Padova, Italy. pp. 396-402. (LNAI 3245)
  51. Lee, S., Yang, J. and Oh, K. (2003.10). Prediction of Molecular Bioactivity for Drug Design Using a Decision Tree Algorithm. Proceedings of the Sixth International Conference on Discovery Science (DS'03). Sapporo, Japan. pp. 344-351. (LNAI 2843)
  52. Yang, J., Chalasani, V. and Park, S. (2003.7). Intelligent Email Categorization Based on Textual Information and Metadata. IEICE Transactions on Information and Systems E86-D(7): 1280-1288.
  53. Yang, J. and Park, S. (2002.11). Email Categorization Using Fast Machine Learning Algorithms. Proceedings of the Fifth International Conference on Discovery Science (DS'02). Lubeck, Germany. pp. 316-323. (LNCS 2534)
  54. Park, S., Yang, J. and Kim, Y. (2002.10). Design and Implementation of Application-Level Multicasting Services over ATM Networks. Proceedings of the First EurAsian Conference on Information and Communication Technology (EurAsia-ICT'02). Shiraz, Iran. pp. 479-486. (LNCS 2510)
  55. Parekh, R., Yang, J. and Honavar, V. (2000). Constructive Neural Network Learning Algorithms for Pattern Classification. IEEE Transactions on Neural Networks 11(2):436-451. 
  56. Parekh, R., Yang, J. and Honavar, V. (2000). An Empirical Comparison of the Performance of Single-layer Algorithms for Training Threshold Logic Units. Journal of Neural, Parallel, and Scientific Compuatation 8:415-438.
  57. Giuffrida, G., Shek, E. and Yang, J. (2000). Knowledge-Based Metadata Extraction from Postscript Files. Proceedings of the Fifth ACM Conference on Digital Libraries (DL'00) , San Antonio, TX.
  58. Chuang, W. and Yang, J. (2000). Extracting Sentence Segments for Text Summarization: A Machine Learning Approach. Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'00). Athens, Greece. pp. 152-159.
  59. Chuang, W. and Yang, J. (2000). Text Summarization by Sentence Segment Extraction Using Machine Learning Algorithms. Proceedings of the Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'00). Kyoto, Japan. pp. 454-457.
  60. Chuang, W., Tiyyagura, A., Yang, J. and Giuffrida, G. (2000). A Fast Algorithm for Hierarchical Text Classification. Proceedings of the Second International Conference on Data Warehousing and Knowledge Discovery (DaWaK'00). London-Greenwich, United Kingdom. pp. 409-418.
  61. Yang, J., Parekh, R. and Honavar, V. (1999). DistAl: An Inter-pattern Distance-based Constructive Learning Algorithm. Intelligent Data Analysis 3: 55-73.
  62. Yang, J., Parekh, R., Honavar, V. and Dobbs, D. (1999). Data-Driven Theory Refinement Using KBDistAl. Proceedings of the Third Symposium on Intelligent Data Analysis (IDA'99). Amsterdam, The Netherlands. pp. 331-342.
  63. Yang, J., Parekh, R., Honavar, V. and Dobbs, D. (1999). Data-Driven Theory Refinement Algorithms for Bioinformatics. Proceedings of the International Joint Conference on Neural Networks (IJCNN'99). Washington D.C. pp. 4064-4068.
  64. Yang, J. and Honavar, V. (1998). Feature Subset Selection Using A Genetic Algorithm. Chapter 8: 117-136. Feature Extraction, Construction and Selection - A Data Mining Perspective. Motoda and Liu (ed.) Kluwer Academic Publishers.
  65. Yang, J. and Honavar, V. (1998). Feature Subset Selection Using A Genetic Algorithm. IEEE Intelligent Systems 13(2): 44-49.
  66. Yang, J. and Honavar, V. (1998). Experiments with the Cascade-Correlation Algorithm. Microcomputer Applications 17(2): 40-46.
  67. Yang, J., Honavar, V., Miller, L. and Wong, J. (1998). Intelligent Mobile Agents for Information Retrieval and Knowledge Discovery from Distributed Data and Knowledge Sources. Proceedings of the IEEE Information Technology Conference. Syracuse, New York. pp. 99-102.
  68. Yang, J., Havaldar, R., Honavar, V., Miller, L. and Wong, J. (1998). Coordination of Distributed Knowledge Networks Using Contract Net Protocol. Proceedings of the IEEE Information Technology Conference. Syracuse, New York. pp. 71-74.
  69. Yang, J., Pai, P., Honavar, V. and Miller, L. (1998). Mobile Intelligent Agents for Document Classification and Retrieval: A Machine Learning Approach. Proceedings of the Fourteenth European Meeting on Cybernetics and Systems Research (EMCSR'98). Vienna, Austria. pp. 707-712.
  70. Yang, J., Parekh, R. and Honavar, V. (1998). DistAl: An Inter-pattern Distance-based Constructive Learning Algorithm. Proceedings of the International Joint Conference on Neural Networks (IJCNN'98). Anchorage, Alaska. pp. 2208-2213.
  71. Yang, J. and Honavar, V. (1997). Feature Subset Selection Using A Genetic Algorithm. Proceedings of the GP-97. Stanford, CA. pp. 380-385.
  72. Parekh, R., Yang, J. and Honavar, V. (1997). MUpstart - A Constructive Neural Network Learning Algorithm for Multi-Category Pattern Classification. Proceedings of the IEEE/INNS International Conference on Neural Networks (ICNN'97), Houston, TX. June 9-12, 97. vol III, pp. 1924-1929.
  73. Parekh, R., Yang, J. and Honavar, V. (1997). Pruning Strategies for the MTiling Constructive Learning Algorithm. Proceedings of the IEEE/INNS International Conference on Neural Networks (ICNN'97), Houston, TX. June 9-12, 97. vol III, pp. 1960-1965.
  74. Yang, J., Parekh, R. and Honavar, V. (1996). MTiling - A Constructive Neural Network Learning Algorithm for Multi-Category Pattern Classification. Proceedings of the World Congress on Neural Networks. San Diego, CA. pp. 182-187.
  75. Yang, J. and Honavar, V. (1996). A Simple Randomized Quantization Algorithm for Neural Network Pattern Classifiers. Proceedings of the World Congress on Neural Networks. San Diego, CA. pp. 223-228.
  76. Chen, C-H., Parekh, R. G., Yang, J., Balakrishnan, K. and Honavar, V. G. (1995). Analysis of Decision Boundaries Generated by Constructive Neural Learning Algorithms. Proceedings of the World Congress on Neural Networks.Washington D.C. pp. 628-635.
  77. Yang, J. and Honavar, V. (1993). A Hierarchical Representation Scheme for Three-Dimensional Object Recognition and Description. Proceedings of FLAIRS-93. Fort Lauderdale, Florida.
  78. Yang, J. and Honavar, V. (1991). Experiments with the Cascade Correlation Algorithm. Proceedings of the Fourth UNB Artificial Intelligence Symposium. Fredericton, Canada. pp. 369-380.