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 |
|---|---|---|
| 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 |
| Date | Title | Speaker |
|---|---|---|
| 12. 27, 2023 | SGCL: Contrastive Representation Learning for Signed Graphs | Kahyun Park |
| 12. 06, 2023 | A scalable optimization approach for fitting canonical tensor decompositions | Jeongyoung Lee |
| 11. 29, 2023 | Chasing Higher FLOPS for Faster Neural Networks | Yong-chan Park |
| 11. 22, 2023 | SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models | Sojin Lee |
| 11. 15, 2023 | Mastering Stock Markets with Efficient Mixture of Diversified Trading Experts | Jihyeong Jeon |
| 11. 08, 2023 | MAPS: Multi-agent Reinforcement Learning-based Portfolio Management System | Jin-gee Kim |
| 11. 01, 2023 | Powerful Graph Convolutioal Networks with Adaptive Propagation Mechanism for Homophily and Heterophily | Junghun Kim |
| 10. 25, 2023 | Knowledge Graph Contrastive Learning for Recommendation | Jongjin Kim |
| 10. 11, 2023 | Translating Embeddings for Modeling Multi-relational Data | Hoyoung Yoon |
| 10. 04, 2023 | Enhancing Stock Movement Prediction with Adversarial Training | Saurav Tanwar |
| 09. 27, 2023 | Contrastive Learning for Sequential Recommendation by Xu Xie et al. (SIGIR’21) | Jeongin Yun |
| 09. 20, 2023 | Fast and Accurate Transferability Measurement by Evaluating Intra-class Feature Variance | Huiwen Xu |
| 09. 13, 2023 | SparseGPT: Massive Language Models Can be Accurately Pruned in One-Shot | Seungcheol Park |
| 09. 06, 2023 | Are Transformers Effective for Time Series Forecasting? | Taehun Kim |
| 08. 23, 2023 | Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States | Jiwon Park |
| 08. 16, 2023 | Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation | Jong-eun Lee |
| 08. 09, 2023 | Teach Less, Learn More: On the Undistillable Classes in Knowledge Distillation | Jaehyeon Choi |
| 07. 26, 2023 | Deep Reinforcement Learning from Human Preferences | Chanhee Park |
| 07. 19, 2023 | Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding | Yejun Soun |
| 07. 12, 2023 | Multi-Behavior Recommendation with Cascading Graph Convolution Networks | Doyeon Kim |
| 07. 05, 2023 | Signed Graph Attention Networks | Kahyun Park |
| 06. 28, 2023 | Global Filter Networks for Image Classification | Yong-chan Park |
| 06. 21, 2023 | Application of Deep Q-Network in Portfolio Management | Jin-gee Kim |
| 06. 07, 2023 | SPADE: Streaming PARAFAC2 Decomposition for Large Datasets | Jeongyoung Lee |
| 05. 31, 2023 | MetaTrader: An Reinforcement Learning Approach Integrating Diverse Policies for Portfolio Optimization | Jihyeong Jeon |
| 05. 17, 2023 | Predict then Propagate: Graph Neural Networks meet Personalized PageRank | Junghun Kim |
| 05. 10, 2023 | Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation | Jongjin Kim |
| 05. 03, 2023 | KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation | Hoyoung Yoon |
| 04. 26, 2023 | Aggregately Diversified Bundle Recommendation via Popularity Debiasing and Configuration-aware Reranking | Hyunsik Jeon |
| 04. 12, 2023 | Stock Price Prediction Using News Sentiment Analysis | Saurav Tanwar |
| 04. 05, 2023 | GSL4Rec: Session-based Recommendations with Collective Graph Structure Learning and Next Interaction Prediction | Jeongin Yun |
| 03. 29, 2023 | Graph Heterogeneous Multi-Relational Recommendation | Jaeri Lee |
| 03. 22, 2023 | Rabbit Holes and Taste Distortion: Distribution-Aware Recommendation with Evolving Interests | Jongjin Kim |
| 03. 15, 2023 | FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling | Huiwen Xu |
| 03. 08, 2023 | A Fast Post-Training Pruning Framework for Transformers | Seungcheol Park |
| 02. 27, 2023 | IOT: Instance-wise Layer Reordering for Transformer Structures | Hyojin Jeon |
| 02. 20, 2023 | CuCo: Graph Representation with Curriculum Contrastive Learning | Sooyeon Shim |
| 02. 13, 2023 | SETN: Stock Embedding Enhanced with Textual and Network Information | Jaemin Park |
| 02. 06, 2023 | NPA: Neural News Recommendation with Personalized Attention | Jiyun Kim |
| 01. 30, 2023 | A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction | Taehun Kim |
| 01. 09, 2023 | DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation | Jiwon Park |
| 01. 02, 2023 | LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation | Jong-eun Lee |