In the data mining seminar, we have talks about various data mining, machine learning, and AI related topics, including data analysis methods, applications, and scalable platforms. The seminar information is as follows.
The contact information for anything related to the seminar is as follows.
During the seminar, free pizza is provided to participants.
| Date | Title | Speaker |
|---|---|---|
| 05. 14, 2025 | DART: Diversified and Accurate Long-Tail Recommendation | Jeongin Yun |
| 05. 07, 2025 | FINCON: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making | Jaemin Hong |
| 04. 30, 2025 | CoCa: Contrastive Captioners are Image-Text Foundation Models | Seung-Ho Kim |
| 04. 09, 2025 | GenQ: Quantization in Low Data Regimes with Generative Synthetic Data | Jongkeun Lee |
| 03. 26, 2025 | SynQ: Accurate Zero-shot Quantization by Synthesis-aware Fine-tuning | Minjun Kim |
| 03. 19, 2025 | TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting | Kisoo Kim |
| 03. 05, 2025 | Sequentially Diversified and Accurate Recommendations in Chronological Order for a Series of Users | Jongjin Kim |
| 02. 26, 2025 | Compact Decomposition of Irregular Tensors for Data Compression: From Sparse to Dense to High-Order Tensors | Jeongyoung Lee |
| 02. 19, 2025 | Time-Aware Random Walk Diffusion to Improve Dynamic Graph Learning | Hoyoung Yun |
| 02. 12, 2025 | Accurate Link Prediction for Edge-Incomplete Graphs via PU Learning | Junghun Kim |
| 02. 05, 2025 | Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction | Saurav Tanwar |
| 01. 22, 2025 | Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System | Jeongin Yun |
| 01. 08, 2025 | A Time Series is Worth 64 Words: Long-term Forecasting with Transformers | Taehoon Kim |
| Date | Title | Speaker |
|---|---|---|
| 11. 27, 2024 | Towards True Multi-interest Recommendation: Enhanced Scheme for Balanced Interest Training | Jaeri Lee |
| 11. 20, 2024 | DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs | Sojin Lee |
| 11. 06, 2024 | Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias | Jong-eun Lee |
| 10. 30, 2024 | DeepCache: Accelerating Diffusion Models for Free | Jaehyeon Choi |
| 10. 16, 2024 | A Simple But Powerful Graph Encoder for Temporal Knowledge Graph Completion | SeungJoo Lee |
| 10. 02, 2024 | Emotion-Anchored Contrastive Learning Framework for Emotion Recognition in Conversation | Chanhee Park |
| 09. 25, 2024 | Modeling Extreme Events in Time Series Prediction | Dongho Lee |
| 09. 11, 2024 | Coupling Macro-Sector-Micro Financial Indicators for Learning Stock Representations with Less Uncertainty | Yejun Soun |
| 09. 04, 2024 | Hard Sample Matters a Lot in Zero-Shot Quantization | Minjun Kim |
| 08. 21, 2024 | FreQuant: A Reinforcement-Learning based Adaptive Portfolio Optimization with Multi-frequency Decomposition | Jihyeong Jeon |
| 08. 14, 2024 | Proximal Policy Optimization Algorithms | Hyunwoo Lee |
| 07. 24, 2024 | Fast Multidimensional Partial Fourier Transform with Automatic Hyperparameter Selection | Yong-chan Park |
| 07. 17, 2024 | Fast and Accurate Domain Adaptation for Irregular Tensor Decomposition | Junghun Kim |
| 07. 10, 2024 | RSGNN: A Model-agnostic Approach for Enhancing the Robustness of Signed Graph Neural Networks | Ka Hyun Park |
| 07. 03, 2024 | MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting | Kisoo Kim |
| 06. 19, 2024 | Hyperspectral Super-Resolution: A Coupled Tensor Factorization Approach | Jeongyoung Lee |
| 06. 05, 2024 | OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models | Sojin Lee |
| 05. 29, 2024 | MASTER: Market-Guided Stock Transformer for Stock Price Forecasting | Jihyeong Jeon |
| 05. 22, 2024 | StockMixer: A Simple Yet Strong MLP-Based Architecture for Stock Price Forecasting | Jin-gee Kim |
| 05. 08, 2024 | LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation | Jongjin Kim |
| 05. 01, 2024 | Language Models as Knowledge Embeddings | Hoyoung Yoon |
| 04. 24, 2024 | Accurate Semi-supervised Automatic Speech Recognition via Multi-hypotheses-based Curriculum Learning | Junghun Kim |
| 03. 27, 2024 | Co-occurrence Embedding Enhancement for Long-tail Problem in Multi-Interest Recommendation | Jeongin Yun |
| 03. 13, 2024 | Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models | Seungcheol Park |
| 03. 06, 2024 | A Transformer-based Framework for Multivariate Time Series Representation Learning | Taehun Kim |
| 02. 28, 2024 | Select and Trade : Towards Unified Pair Trading with Hierarchical Reinforcement Learning | Jiwon Park |
| 02. 21, 2024 | How Attentive are Graph Attention Networks? | Jong-eun Lee |
| 02. 14, 2024 | Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation | Jaehyeon Choi |
| 02. 07, 2024 | Graph Structure Aware Contrastive Knowledge Distillation for Incremental Learning in Recommender Systems | Seungjoo Lee |
| 01. 31, 2024 | StockFormer: Learning Hybrid Trading Machines with Predictive Coding | Chanhee Park |
| 01. 24, 2024 | Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction | Yejun Soun |
| 01. 17, 2024 | ifMixup: Interpolating Graph Pair to Regularize Graph Classification | Minjun Kim |
| 01. 10, 2024 | Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport | Hyunwoo Lee |
| 01. 03, 2024 | Sequential Recommendation with Graph Neural Networks | Jaeri Lee |