Miscellaneous62 [2025-2] 박지원 - GPTQ 논문) https://arxiv.org/abs/2210.17323 GPTQ: Accurate Post-Training Quantization for Generative Pre-trained TransformersGenerative Pre-trained Transformer models, known as GPT or OPT, set themselves apart through breakthrough performance across complex language modelling tasks, but also by their extremely high computational and storage costs. Specifically, due to their massarxiv.org 1. GPTQ란 GPTQ.. 2025. 7. 1. [2025-1] 유경석 - nnDetection: A Self-configuring Method for Medical Object Detection https://arxiv.org/abs/2106.00817 nnDetection: A Self-configuring Method for Medical Object DetectionSimultaneous localisation and categorization of objects in medical images, also referred to as medical object detection, is of high clinical relevance because diagnostic decisions often depend on rating of objects rather than e.g. pixels. For this task, tharxiv.orghttps://github.com/MIC-DKFZ/nnDet.. 2025. 5. 24. [2025-1] 이루가 - Machine learning based recommender system for e-commerce 논문 링크: https://www.researchgate.net/publication/373328673_Machine_learning_based_recommender_system_for_e-commerce 0. Abstract전자상거래의 핵심 성공 요소 중 하나는 맞춤형 상품 추천추천 시스템은 사용자 경험을 향상시키고 구매율을 높임본 연구에서는 FP-Growth 기반의 연관 규칙 알고리즘을 사용추천된 상품의 평균 구매 확률이 높아 실제 적용 가능성 있음 1. Introduction오늘날 디지털 기술의 발전과 인터넷 접근의 용이성 덕분에 우리는 점점 더 많은 정보에 노출 → 사용자에게 다양한 콘텐츠를 제공하지만, 동시에 정보 과잉과 다수의 정보 출처로 인해 혼란 초래이러한 문제의 해결을 위해서 사용자에게 .. 2025. 5. 10. [2025-1] 박제우 - Deep Anomaly Detection with Deviation Networks https://arxiv.org/abs/1911.08623 Deep Anomaly Detection with Deviation NetworksAlthough deep learning has been applied to successfully address many data mining problems, relatively limited work has been done on deep learning for anomaly detection. Existing deep anomaly detection methods, which focus on learning new feature representaarxiv.org Deep Anomaly Detection with Deviation NetworksAlthoug.. 2025. 4. 6. 이전 1 2 3 4 ··· 16 다음
