hyoseok1223 / ai-study

연구 내용 공유 및 AI 논문 스터디

AI-Study

인공지능 논문 스터디

1. 스터디 안내

• 일시: 매주 수요일 9:00 PM
• 내용: 연구 주제 발표 및 논문 리뷰
• 목적: 다양한 분야의 최신 트렌드 파악 및 AI 지식 저변 확대
  
  

2. 스터디 멤버

• 임진혁: Knowledge Distillation, Meta Learning, Few Shot Learning, Self-supervised Learning, Domain Generalization, Federate Learning
• 최영제: Machine Learning, Reinforcement Learning, Auto Feature Engineering, Time Series Forecasting, Anomaly Detection
  
  

Paper List

Date	Paper	Topic	Presenter	Links	Needs futher modification
2020.04.16	[CVPR 2019] SpotTune, Transfer learning through adaptive fine-tuning	Vision, Transfer Learning	최영제	paper review blog	X
2020.04.23	[NIPS 2015] Distilling the Knowledge in a Neural Network	Knowledge Distillation	임진혁	paper review	O
2020.05.14	[CVPR 2019] Class-Balanced Loss Based on Effective Number of Samples	Class Imbalance	최영제	paper review blog	X
2020.05.20	[KDD 2018] Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System	Recommeder System Knowledge Distillation	임진혁	paper review	O
2020.07.02	[NIPS 2019] Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models	Time Series Forecasting	최영제	paper review	X
2020.07.08	[ICML 2020] Rethinking Data Augmentation: Self-Supervision and Self-Distillation	Augmentation Self-Supervised Learning	임진혁	paper review	O
2020.07.16	[ICLR 2020] Distance based learning from errors for confidence calibration	Model Calibration	최영제	paper review blog	X
2020.07.23	[NIPS 2019] Knowledge Extraction with No Observable Data	Knowledge Disillation	임진혁	paper review	O
2021.02.25	[NIPS 2020] Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs	GNN Self-Supervised Learning	임진혁	paper review	O
2021.02.25	[ICML 2018] GAIN Missing Data Imputation using Generative Adversarial Nets	Data Imputation	최영제	paper review blog	X
2021.03.04	[AISTATS 2017] Communication-Efficient Learning of Deep Networks from Decentralized Data	Federate Learning	임진혁	paper review	O
2021.03.11	Reinforcement learning 01 - MDP, Q-learning	Reinforcement Learning	최영제	review	O
2021.03.18	[NIPS 2019] FedMD: Heterogenous Federated Learning via Model Distillation	Federate Learning, Knowledge Distillation	임진혁	paper review	O
2021.03.18	Reinforcement learning 02 - DQN, PER, Dueling DQN	Reinforcement Learning	최영제	review blog	X
2021.03.25	[ICML 2017] Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	Meta Learning Few Shot	임진혁	paper review	O
2021.03.25	Reinforcement learning 03 - PG, Actor-critic, A2C	Reinforcement Learning	최영제	review	X
2021.03.31	[ICLR 20201] DOMAIN GENERALIZATION WITH MIXSTYLE	Domain Generalization	임진혁	paper review	O
2021.03.31	Reinforcement learning 04 - A3C, SIL	Reinforcement Learning	최영제	review	X
2021.04.07	[arXiv 2021] Meta Pseudo Labels	Semi-Supervised Learning	임진혁	paper review	O
2021.04.07	[ICLR 2017] Neural architecture search with reinforcement learning	AutoML	최영제	paper review	X
2021.05.12	[CVPR 2020] Attentive Weights Generation for Few Shot Learning via Information Maximization	Few Shot Attention	임진혁	paper review	O
2021.05.12	[ICML 2018] Efficient nerual architecture search via parameter sharing	AutoML	최영제	paper review	X
2021.05.25	[ICLR 2015] ADAM : A METHOD FOR STOCHASTIC OPTIMIZATION	Optimization	임진혁	paper review	O
2021.05.25	[arXiv 2020] DIFER, Differentiable automated feature engineering	AutoFE	최영제	paper review	X
2021.06.09	[KDD 2020] USAD, unsupervised anomaly detection on multivariate time series	Anomaly Detection	최영제	paper review blog	X
2021.06.16	[ICML 2019] Zero-Shot Knowledge Distillation in Deep Networks	Knowledge Distillation Few Shot	임진혁	paper review	O
2021.06.23	[arXiv 2018] Federated Meta-Learning with Fast Convergence and Efficient Communication	Federate Learning Meta Learning	임진혁	paper review	O
2021.06.23	[IEEE ICBD 2020] TadGAN, Time series anomaly detection using generative adversarial networks	Anomaly Detection	최영제	paper review	X
2021.06.30	[ICLR 2021] BOIL: TOWARDS REPRESENTATION CHANGE FOR FEW-SHOT LEARNING	Meta Learning Few Shot	임진혁	paper review	O
2021.06.30	[ICDM 2019] Neural feature search, A nueral architecture for automated feature enigneering	AutoFE	최영제	paper review	X
2021.07.07	[arXiv 2018] Exploration by Random Network Distillation	Reinforcement Learning	최영제	paper review	X
2021.07.16	[NIPS 2019] Domain Generalization via Model-Agnostic Learning of Semantic Features	Domain Generalization Meta Learning	임진혁	paper review	X
2021.07.21	[PAKDD 2020] Cross data Automatic Feature Engineering via Meta learning and Reinforcement Learning	AutoFE	최영제	paper review	X
2021.08.04	[arXiv 2017] PathNet, Evolution Channels Gradient Descent in Super Neural Networks	Transfer Learning	최영제	paper review	X