Data Mining Lab.
Welcome to Data Mining Laboratory in the Department of Computer Science and Engineering at Seoul National University. Our research interests lie in artificial intelligence (AI), data mining, and machine learning to find models, algorithms, and systems for data analysis. Specifically, we focus on the following research topics: deep learning & machine learning, recommender & QA systems, graphs/tensors, and financial AI.
What's New
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[May. 2025] A paper accepted to ACL 2025, a top tier AI conference.
A paper accepted to ACL 2025, a top tier AI conference. The paper "Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models" proposed UniQuanF, an accurate quantization method for LLMs by unifying uniform and binary-coding quantization.
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[May. 2025] 2 papers accepted to KDD 2025, the world-best data science and AI conference.
2 papers from Data Mining Lab are accepted to KDD 2025, the world-best data science and AI conference. Congratulations!
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[May 2025] 2 papers accepted to accepted to IJCAI 2025, a top tier AI conference.
2 papers from Data Mining Lab are accepted to IJCAI 2025, a top tier AI conference. Congratulations!
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[Feb. 2025] 2 papers accepted to PAKDD 2025, a top tier data mining conference.
2 papers from Data Mining Lab are accepted to PAKDD 2025, a top tier data mining conference. Congratulations!
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[Jan. 2025] A paper accepted to ICLR 2025, a top tier AI conference.
A paper accepted to ICLR 2025, a top tier AI conference. The paper “SynQ: Accurate Zero-shot Quantization by Synthesis-aware Fine-tuning” proposed SynQ, an accurate zero-shot quantization method applicable to any existing methods that fine-tune with synthetic datasets.