Paper#
Title |
Journal/Conference |
Year |
Description |
νκ·Έ |
νμΌ |
Slide |
Reviewer |
Youtube |
XMind |
|---|---|---|---|---|---|---|---|---|---|
Zero-shot learning through cross-modal transfer |
NIPS |
2013 |
Zero-shot learning |
Machine Learning Basics |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/5027-zero-shot-learning-through-cross-modal-transfer.pdf |
κΉμλΉ(PYMR) |
https://www.youtube.com/watch?v=3LJz44iDuXs |
Included |
|
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling |
arXiv |
2014 |
GRU, LSTM, RNN |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1412.3555.pdf |
κΉνμ°(PYMR) |
https://www.youtube.com/watch?v=5Ar1aN9gceg |
Included |
|
Semi-supervised Learning with Deep Generative Models |
2014 |
Semi-supervised Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/5352-semi-supervised-learning-with-deep-generative-models.pdf |
μν(PYMR) |
https://www.youtube.com/watch?v=5Hyql-1amPU |
Included |
|||
YOLOv4: Optimal Speed and Accuracy of Object Detection |
arXiv |
2020 |
Yolo-V4 |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/2004.10934.pdf |
νμ¬ν(PYMR) |
https://www.youtube.com/watch?v=6f7jglewoWg |
Included |
|
TextRank: Bringing Order into Texts |
EMNLP |
2004 |
Summarization |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/mihalcea.emnlp04.pdf |
κ³ μ κ²½(PYMR) |
https://www.youtube.com/watch?v=AxXD4IbG6PI&list=PLetSlH8YjIfUpPbSAfsY4zBJfztlH9CSQ&index=4 |
Included |
|
Recent trends in deep learning based natural language processing |
arXiv |
2017 |
Review Paper |
NLP, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Recent_Trends_in_Deep_Learning_Based_NLP.pdf |
κ³ μ κ²½(PYMR) |
https://www.youtube.com/watch?v=B3qd3LgsTRY |
Included |
|
Long Short-Term Memory |
Neural Computation |
1997 |
LSTM |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1_LSTM.pdf |
λ₯μΉν(PYMR) |
https://www.youtube.com/watch?v=IgIHjiCgECw |
Included |
|
Rich feature hierarchies for accurate object detection and semantic segmentation |
ICCV |
2014 |
R-CNN, Object Detection |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1311.2524.pdf |
λ°μ§μ°(PYMR) |
https://www.youtube.com/watch?v=kKDJXMZRNe4 |
Included |
|
World Models |
arXiv |
2018 |
Reinforcement Learning |
Reinforcement Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1803.10122.pdf |
κ°νμ(PYMR) |
https://www.youtube.com/watch?v=qm9kW9M4QyA&t=1123s |
Included |
|
ADAM: A Method for Stochastic Optimization |
ICLR |
2015 |
Neural Network Training |
Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1412.6980.pdf |
κΉμ€ν(PYMR) |
https://www.youtube.com/watch?v=sIjVu2xnTfI |
Included |
|
Advances in natural language processing |
Science |
2015 |
Review Paper |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/HirschbergManning15_SCIENCE_Advances_in_natural_language_processing.pdf |
νμ±ν¬(PYMR) |
https://www.youtube.com/watch?v=VbogeLagy4A |
Included |
|
A Review of Novelty Detection |
Signal Processing |
2014 |
Anomaly Detection |
Anomaly Detection, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/A_Review_of_Novelty_Detection.pdf |
μ΅μ μ°(PYMR) |
https://www.youtube.com/watch?v=VkOQST5pf0o&t=549s |
Included |
|
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning |
ICML |
2016 |
Uncertainty Estimation, Bayesian Deep Learning |
Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1506.02142.pdf |
μ μ©κΈ°(PYMR) |
https://www.youtube.com/watch?v=VuUYuhXWpws |
Not included |
|
Going deeper with convolutions |
ICCV |
2015 |
GoogleNet |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1409.4842.pdf |
μμΉμ(PYMR) |
https://www.youtube.com/watch?v=W9MlakX3vko |
Included |
|
Human-level control through deep reinforcement learning |
Nature |
2015 |
Artificial Intelligence, Reinforcement Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Mnih15_NATURE_Human-level_control_through_deep_reinforecement_learning.pdf |
κ°νμ(PYMR) |
https://www.youtube.com/watch?v=XdG6L5Hd06M&t=588s |
Included |
||
AutoML: A Survey of the State-of-the-Art |
arXiv |
2019 |
Auto-ML |
Auto-ML |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/AutoML_A_Survey_of_the_State-of-the-Art.pdf |
μ μ©κΈ°(PYMR) |
https://www.youtube.com/watch?v=z3dIbE586JE&t |
Included |
|
Convolutional neural networks for sentence classification |
EMNLP |
2014 |
CNN-based document classification |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/D14-1181.pdf |
μ΄κΈ°μ°½(μΈλ―Έλ) |
https://youtu.be/_0bOjspRG6s |
Included |
|
An overview of gradient descent optimization algorithms |
arXiv |
2016 |
Gradient Descent |
Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1609.04747.pdf |
κ°νμ(PYMR) |
https://youtu.be/0ro4iuilntY |
Included |
|
The PageRank citation ranking: Bringing order to the web |
1999 |
PageRank |
Data Mining |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1999-66.pdf |
μ€νμ(PYMR) |
https://youtu.be/2CWnZfBSj0Q |
Included |
||
An introduction to ROC analysis |
Pattern Recognition Letters |
2006 |
ROC Curve |
Machine Learning Basics |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/2._An_Introduction_to_ROC_Analysis.pdf |
μ€νμ(PYMR) |
https://youtu.be/2IJROWTPs9k |
Included |
|
CatBoost : unbiased boosting with categorical features |
NIPS |
2018 |
CatBoost |
Ensemble Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/CatBoost_unbiased_boosting_with_categorical_features.pdf |
κΉμ§λ(PYMR) |
https://youtu.be/2Yi_Jse_7JQhttps://youtu.be/-w_6wDJQCZY |
Included |
|
LightGBM: A Highly Efficient Gradient Boosting Decision Tree |
NIPS |
2017 |
LightGBM |
Ensemble Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/4C8SUZJPlMY |
Included |
|
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift |
arXiv |
2015 |
Batch Normalization |
Deep Learning, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1502.03167.pdf |
κΉνμ(PYMR) |
https://youtu.be/4jAyXi7byd8 |
Included |
|
Combining Labeled and Unlabeled Data with Co-Training |
1998 |
Co-Training |
Semi-supervised Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/cotrain.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/5i-wVc8Jn-U |
Included |
||
Effective Approaches to Attention-based Neural Machine Translation |
arXiv |
2015 |
Attention |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1508.04025.pdf |
μκ·μ±(PYMR) |
https://youtu.be/5zc1v1qUmMc |
Included |
|
Language models are unsupervised multitask learners |
2019 |
GPT-2 |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/2019-Radford-et-al_Language-Models-Are-Unsupervised-Multitask-_Learners.pdf |
μ΄μ κ²½(μΈλ―Έλ) |
https://youtu.be/8hd2Q-3-BsQ, https://youtu.be/d05ype2cVQc |
Included |
||
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing |
ICML |
2016 |
Question Answering |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1506.07285.pdf |
κΉμ§λ(PYMR) |
https://youtu.be/8uGpr-WyWlI |
Included |
|
Enriching word vectors with subword information |
arXiv |
2016 |
FastText |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Enriching_word_vectors_with_subword_information.pdf |
κΉμλΉ(PYMR) |
https://youtu.be/bvSHJG-Fz3Y https://youtu.be/7UA21vg4kKE |
Included |
|
Efficient Estimation of Word Representations in Vector Space |
2013 |
Word2Vec |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1312.5650.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/bvSHJG-Fz3Yhttps://youtu.be/sidPSG-EVDo |
Included |
||
Squad: 100,000+ questions for machine comprehension of text |
arXiv |
2016 |
Question Answering |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1606.05250.pdf |
μ‘°κ·μ(μΈλ―Έλ) |
https://youtu.be/CbY_xcBGR20, https://youtu.be/7u6Ys7I0z2E |
Included |
|
End-To-End Memory Networks |
NIPS |
2015 |
Memory Network |
Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1503.08895.pdf |
νμ¬ν(PYMR) |
https://youtu.be/CM5lRnNad2Q |
Included |
|
Dropout: A Simple Way to Prevent Neural Networks from Over-fitting |
Journal of Machine Learning Research |
2014 |
Neural Network Training |
Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/SrivastavaETAL14_Dropout_A_Simple_Way_to_Prevent_Neural_Networks_from_Overfitting.pdf |
μ΅μ μ°(PYMR) |
https://youtu.be/czSKnb4nDu8 |
Included |
|
Gradient Boosting Machine, A Tutorial |
Frontiers in Neurorobotics |
2013 |
GBM |
Ensemble Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/GBM_Tutorial.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/d6nRgztYWQM |
Included |
|
Greedy Function Approximation: A Gradient Boosting Machine |
Annals of Statistics |
2001 |
GBM |
Ensemble Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Greedy_Function_Approximation_A_Gradient_Boosting_Machine.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/d6nRgztYWQM |
Included |
|
Machine learning: Trends, perspectives, and prospects |
Science |
2015 |
Machine Learning Basics |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/JordanMitchell15_SCIENCE_Machine_learning_Trends_perspectives_and_prospects.pdf |
κΉμ μ°(PYMR) |
https://youtu.be/d9NlDHJBrnI |
Included |
||
Distributed representations of words and phrases and their compositionality |
NIPS |
2013 |
Skip-gram |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf |
κΉλμ€(PYMR) |
https://youtu.be/deC3Qjiw0E0 |
Included |
|
A Tutorial on Support Vector Machine for Pattern Recognition |
Technical Report |
1998 |
SVM |
Kernel Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/A_Tutorial_on_Support_Vector_Machines_for_Pattern_Recognition(Burges).pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/eZtrD6pYaaE, https://youtu.be/RKMiTJAnLy8 |
Included |
|
Semi-Supervised Classification with Graph Convolutional Networks |
ICLR |
2017 |
SSL, GCN |
Graph, Semi-supervised Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1609.02907.pdf |
μ€νμ(PYMR) |
https://youtu.be/F-JPKccMP7k |
Included |
|
Group normalization |
ECCV |
2018 |
Normalization |
Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Yuxin_Wu_Group_Normalization_ECCV_2018_paper.pdf |
κΉμ μ(PYMR) |
https://youtu.be/fJ9U2zvp2Jk |
Included |
|
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches |
2014 |
GRU, RNN |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1409.1259.pdf |
κΉμ§λ(PYMR) |
https://youtu.be/gbvRiPSIqn4 |
Included |
||
Densely Connected Convolutional Networks |
ICCV |
2017 |
DenseNet |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1608.06993.pdf |
κΉνΈμ(PYMR) |
https://youtu.be/GKo6McozI0o |
Included |
|
An Introduction to Kernel-based Learning Algorithms |
IEEE T. Neural Networks |
2001 |
SVM/SVR/1-SVM/KFDA/KPCA |
Kernel Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/An_Introduction_to_kernel-based_learning_algorithms.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/gzbafL28vA0, https://youtu.be/eZtrD6pYaaE, https://youtu.be/RKMiTJAnLy8, https://youtu.be/zLgQUaXFbQI, https://youtu.be/XpkOcsGTS8k, https://youtu.be/6Et6S03Me4o |
Included |
|
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles |
NIPS |
2017 |
Uncertainty Estimation |
Ensemble Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/NIPS-2017-simple-and-scalable-predictive-uncertainty-estimation-using-deep-ensembles-Paper.pdf |
μ΄μ ν(PYMR) |
https://youtu.be/huh4o6iNamo |
Not included |
|
Visualizing data using t-SNE |
JMLR |
2008 |
t-SNE |
Dimensionality Reduction |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Visualizing_Data_using_t-SNE.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/INHwh8k4XhM |
||
Bert: Pre-training of deep bidirectional transformers for language understanding |
arXiv |
2018 |
BERT |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1810.04805.pdf |
κ°νμ±κ΅μλ(κ°μ), κΉλν(μΈλ―Έλ), μ΄μ κ²½(μΈλ―Έλ) |
https://youtu.be/IwtexRHoWG0, https://youtu.be/xhY7m8QVKjohttps://youtu.be/d05ype2cVQc |
Included |
|
Probabilistic latent semantic analysis |
1999 |
pLSA |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Probabilistic_Latent_Semantic_Analysis.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/J1ri0EQnUOg |
Included |
||
An introduction to latent semantic analysis |
Discourse processes |
1998 |
LSA |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/An_introduction_to_latent_semantic_analysis.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/J1ri0EQnUOg |
Included |
|
Indexing by latent semantic analysis |
Journal of the American society for information science |
1990 |
LSA |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/DeerwesterETAL_Indexing_by_Latent_Semantic_Analysis.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/J1ri0EQnUOg |
||
Probabilistic Topic Models |
Communications of the ACM |
2012 |
Topic Models |
NLP |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/J1ri0EQnUOg |
Included |
||
Generative Adversarial Networks |
NIPS |
2014 |
GAN |
Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1406.2661.pdf |
μκ·μ±(PYMR) |
https://youtu.be/jB1DxJMUlxY |
Included |
|
Fast R-CNN |
ICCV |
2015 |
Fast R-CNN, Object Detection |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1504.08083.pdf |
μμ°μ(μΈλ―Έλ) |
https://youtu.be/Jo32zrxr6l8 |
Included |
|
YOLOv3: An Incremental Improvement |
arXiv |
2018 |
Yolo-V3 |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1804.02767.pdf |
κΉμ μ(PYMR) |
https://youtu.be/jqykPH3jbic |
Included |
|
Learning from imbalanced data |
IEEE TKDE |
2009 |
Class Imbalance |
Machine Learning Basics |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/05128907.pdf |
κΉμμ§(PYMR) |
https://youtu.be/kkJirPwScQQ |
Included |
|
Learning deep features for discriminative localization |
CVPR |
2016 |
Localization |
Deep Learning, Vision, XAI |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Zhou_Learning_Deep_Features_CVPR_2016_paper.pdf |
κΉνμ(PYMR) |
https://youtu.be/KzpSM6erO6c |
Included |
|
Statistical Modeling: The Two Cultures |
Statistical Science |
2001 |
Machine Learning Basics |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/(Breiman)_Statistical_ModelingβThe_Two_Cultures.pdf |
κΉμμ§(PYMR) |
https://youtu.be/lS6KqOqx6bc |
Included |
||
WaveNet: A Generative Model for Raw Audio |
arXiv |
2016 |
Audio, Time-series |
Audio, Time-series |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1609.03499.pdf |
κΉλν(μΈλ―Έλ) |
https://youtu.be/MNZepE1m-kI |
Included |
|
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence |
arXiv |
2020 |
FixMatch |
Semi-supervised Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/2001.07685.pdf |
μ΄μ ν(μΈλ―Έλ) |
https://youtu.be/mXiPbkyGJ9g |
Included |
|
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring |
arXiv |
2019 |
ReMixMatch |
Semi-supervised Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1911.09785.pdf |
μ΄μ ν(μΈλ―Έλ) |
https://youtu.be/mXiPbkyGJ9g |
Included |
|
MixMatch: A Holistic Approach to Semi-Supervised Learning |
NIPS |
2019 |
MixMatch |
Semi-supervised Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1905.02249.pdf |
μ΄μ ν(μΈλ―Έλ) |
https://youtu.be/nSJP7bn2D1U |
Included |
|
Random Forests |
Machine Learning |
2001 |
Random Forest |
Ensemble Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Breiman2001_Article_RandomForests.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/nu_6PB1v3Xk |
Included |
|
Layer normalization |
arXiv |
2016 |
Layer Normalization |
Deep Learning, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1607.06450.pdf |
κΉλμ€(PYMR) |
https://youtu.be/NyPtpanAGqo |
Included |
|
U-Net: Convolutional Networks for Biomedical Image Segmentation |
MICCAI |
2015 |
Image Segmentation |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1505.04597.pdf |
μ μμ(PYMR) |
https://youtu.be/O_7mR4H9WLk |
Included |
|
Improving language understanding by generative pre-training |
2018 |
GPT |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/language_understanding_paper.pdf |
κ°νμ±κ΅μλ(κ°μ), μ΄μ€μΉ(PYMR) |
https://youtu.be/o_Wl29aW5XM https://youtu.be/4qv_ofZN5_U |
Included |
||
You Only Look Once: Unified, Real-Time Object Detection |
ICCV |
2016 |
Yolo-V1 |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1506.02640.pdf |
μ΄μ€μΉ(PYMR) |
https://youtu.be/O78V3kwBRBk |
Included |
|
LOF: Identifying Density-Based Local Outliers |
ACM SIGMOD |
2000 |
LOF |
Anomaly Detection |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/LOF.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/ODNAyt1h6Eg |
Included |
|
Support Vector Data Description |
Machine Learning |
2004 |
SVDD |
Kernel Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Support_Vector_Data_Description.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/OmK_GQ40yko |
Included |
|
Sequence to sequence learning with neural networks |
NIPS |
2014 |
Seq2Seq Learning |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/5346-sequence-to-sequence-learning-with-neural-networks.pdf |
μ΄μ€μΉ(PYMR) |
https://youtu.be/PipiRRL50p8 |
Included |
|
Isolation Forest |
ICDM |
2009 |
Isolation Forest |
Anomaly Detection |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/icdm08b.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/puVdwi5PjVA |
Included |
|
Isolation-based Anomaly Detection |
ACM TKD |
2011 |
Isolation Forest |
Anomaly Detection |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/tkdd11.pdf |
κ°νμ±κ΅μλ(κ°μ), μ΅μ μ°(PYMR) |
https://youtu.be/puVdwi5PjVA, https://youtu.be/_GiER-8nLFc |
Included |
|
A density-based algorithm for discovering clusters in large spatial databases with noise |
KDD |
1996 |
DBSCAN |
Clustering |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/KDD96-037.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/PuVH38UpgNU |
Included |
|
Glove: Global vectors for word representation |
EMNLP |
2014 |
GloVe |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Glove_Global_vectors_for_word_representation.pdf |
κ°νμ±κ΅μλ(κ°μ), μ‘°κ·μ(μΈλ―Έλ) |
https://youtu.be/s2KePv-OxZM, https://youtu.be/8wG0sJm1EaU |
Included |
|
Neural Machine Translation by Jointly Learning to Align and Translate |
ICLR |
2015 |
Attention |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1409.0473.pdf |
κΉνμ(PYMR) |
https://youtu.be/S2msiG9g7Us |
Included |
|
Learning Phrase Representations using RNN EncoderβDecoder for Statistical Machine Translation |
2014 |
Seq2Seq Learning |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1406.1078v1.pdf |
κΉμ ν¬(PYMR) |
https://youtu.be/T-w0X0R0pPY |
Included |
||
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization |
ICCV |
2017 |
Localization, XAI |
Deep Learning, Vision, XAI |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1610.02391.pdf |
μκ·μ±(PYMR) |
https://youtu.be/uA5rIr79I0o |
Included |
|
Know what you donβt know: Unanswerable questions for SQuAD |
arXiv |
2018 |
Question Answering |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1806.03822.pdf |
κΉνμ(μΈλ―Έλ) |
https://youtu.be/uIoXJcsPj_8 |
Included |
|
VQA: Visual Question Answering |
ICCV |
2015 |
Visual Question Answering |
NLP, Vision |
μ΄μ€μΉ(PYMR) |
https://youtu.be/uY6cWyG0JRQ |
Included |
||
XGBoost: A Scalable Tree Boosting System |
ACM SIGKDD |
2016 |
XGBoost |
Ensemble Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1603.02754.pdf |
κ°νμ±κ΅μλ(κ°μ), μ€νμ(PYMR) |
https://youtu.be/VHky3d_qZ_E, https://youtu.be/VkaZXGknN3g |
Included |
|
YOLO9000: Better, Faster, Stronger |
ICCV |
2017 |
Yolo-V2 |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1612.08242.pdf |
μ΄μ€μΉ(PYMR) |
https://youtu.be/vLdrI8NCFMs |
Included |
|
Visualizing and understanding convolutional networks |
ECCV |
2014 |
ZFNet, CNN |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1311.2901.pdf |
μ μμ(PYMR) |
https://youtu.be/vRtM4K8e_Q4 |
Included |
|
Deep residual learning for image recognition |
ICCV |
2016 |
ResNet |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1512.03385.pdf |
μ μμ(PYMR) |
https://youtu.be/vRtM4K8e_Q4 |
Included |
|
Imagenet classification with deep convolutional neural networks |
NIPS |
2012 |
CNN, AlexNet |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf |
μ μμ(PYMR) |
https://youtu.be/vRtM4K8e_Q4 |
Included |
|
Very Deep Convolutional Networks for Large-Scale Image Recognition |
ICLR |
2015 |
VGGNet |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1409.1556.pdf |
μ μμ(PYMR) |
https://youtu.be/vRtM4K8e_Q4 |
Included |
|
Memory Networks |
ICLR |
2015 |
Memory Network |
Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1410.3916.pdf |
κΉμ§λ(PYMR) |
https://youtu.be/w-XiYQmNixA |
Included |
|
Lifelong Learning with Dynamically Expandable Networks |
ICLR |
2018 |
Transfer Learning |
Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1708.01547.pdf |
μ΅ν¬μ (μΈλ―Έλ) |
https://youtu.be/WakxMwYHG4o |
Included |
|
A Neural Attention Model for Abstractive Sentence Summarization |
arXiv |
2015 |
Summarization |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1509.00685.pdf |
μ΄μ κ²½(PYMR) |
https://youtu.be/wfVSjv3yVEQ |
Included |
|
Representation learning: A review and new perspectives |
IEEE TPAMI |
2012 |
Representation Learning |
Deep Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/BengioETAL_Representation_learning_A_review_and_new_perspectives.pdf |
κΉλν(PYMR) |
https://youtu.be/WplrAk0ebrg |
Included |
|
Latent Dirichlet Allocation |
JMLR |
2003 |
LDA |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Latent_Dirichlet_Allocation.pdf |
κ°νμ±κ΅μλ(κ°μ), μ€νμ(PYMR) |
https://youtu.be/WR2On5QAqJQhttps://youtu.be/iwMSCsiL6wQhttps://youtu.be/4AGjlcEQ6I8 |
Included |
|
Deep Learning for Anomaly Detection: A Survey |
arXiv |
2019 |
Anomaly Detection |
Anomaly Detection, Deep Learning, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1901.03407.pdf |
λ°κ²½μ°¬(PYMR) |
https://youtu.be/wSgnhxZ3iQo |
Included |
|
On Clustering Validation Techniques |
Journal of Intelligent Information Systems |
2001 |
Clustering Validity |
Clustering, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/On_clustering_validation_techniques.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/X6kCkqQPRvE |
Included |
|
LSTM: A Search Space Odyssey |
IEEE TNNLS |
2015 |
LSTM, RNN |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1503.04069.pdf |
κΉνμ°(PYMR) |
https://youtu.be/xajFH6tgihg |
Included |
|
Googleβs Neural Machine Translation System: Bridging the Gap between Human and Machine Translation |
arXiv |
2016 |
Machine Translation |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1609.08144.pdf |
κΉνμ(PYMR) |
https://youtu.be/XMOtdAP_AHY |
Included |
|
Language Models are Few-Shot Learners |
arXiv |
2020 |
GPT-3 |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/2005.14165.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/xNdp3_Zrr8Q |
Included |
|
Fast Algorithm for Mining Association Rules |
VLDB |
1994 |
Association Rules, A-Priori |
Data Mining |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Fast_Algorithm_for_Mining_Association_Rules.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/Y1ZphMeDjPA |
Included |
|
A short introduction to boosting |
1999 |
Ensemble, Boosting |
Ensemble Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/FreundSchapire99_A_short_introduction_to_boosting.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/Y2rsmO6Nr4I |
Included |
||
A Neural Probabilistic Language Model |
Journal of Machine Learning Research |
2003 |
NNLM, Word Embedding, Language Model |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/bengio03a.pdf |
κΉνμ(PYMR) |
https://youtu.be/ycxZORWPPP4 |
Included |
|
Attention is all you need |
NIPS |
2017 |
Transformer |
NLP, Neural Network |
κ°νμ±κ΅μλ(κ°μ), κΉλν(μΈλ―Έλ), μκ·μ±(PYMR) |
https://youtu.be/Yk1tV_cXMMUhttps://youtu.be/xhY7m8QVKjohttps://youtu.be/x_8cp4Vdnak |
Included |
||
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks |
NIPS |
2015 |
Faster R-CNN, Object Detection |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1506.01497.pdf |
μκ·μ±(PYMR), μμ°μ(μΈλ―Έλ) |
https://youtu.be/ZhvU7D_qKO8, https://youtu.be/Jo32zrxr6l8 |
Included |
|
Technical Report |
1998 |
SVR |
Kernel Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/A_Tutorial_on_Support_Vector_Regression.pdf |
κ°νμ±κ΅μλ(κ°μ) |
https://youtu.be/zLgQUaXFbQI |
Included |
||
Mastering the game of Go with deep neural networks and tree search |
Nature |
2016 |
AlphaGo |
Artificial Intelligence |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/nature16961.pdf |
κΉνΈμ(PYMR) |
https://youtu.be/zR03u9qlJ3w |
Included |
|
Deep contextualized word representations |
arXiv |
2018 |
ELMo |
NLP, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1802.05365.pdf |
κ°νμ±κ΅μλ(κ°μ), μ΄μ κ²½(μΈλ―Έλ) |
https://youtu.be/zV8kIUwH32M, https://youtu.be/d05ype2cVQc |
Included |
|
An Introduction to Deep Reinforcement Learning |
FTML |
2018 |
Reinforcement Learning |
Reinforcement Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1811.12560.pdf |
Included |
|||
Dimension Reduction: A Guided Tour |
Foundations and Trends in Machine Learning |
2009 |
Dimensionality Reduction |
Dimensionality Reduction, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Burges_Dimension_reduction_A_guided_tour.pdf |
Included |
|||
Interestingness Measures for Data Mining: A Survey |
ACM Computing Surveys |
2006 |
Various quantitative metrics |
Data Mining, Machine Learning Basics, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/3._Interestingness_Measures_for_Data_Mining_A_Survey.pdf |
Included |
|||
Deep learning |
Nature |
2015 |
Deep learning |
Deep Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/LeCunETAL15_NATURE_Deep_learning.pdf |
Included |
|||
A Survey of Parallel Sequential Pattern Mining |
ACM TKDD |
2019 |
Sequential Pattern Mining |
Data Mining |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/3314107.pdf |
Included |
|||
Variational inference: A review for statisticians |
JASA |
2017 |
Variational Inference |
Machine Learning Basics |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/BleiKucukelbirMcAuliffe2017.pdf |
Included |
|||
Overfeat: Integrated recognition, localization and detection using convolutional networks |
arXiv |
2013 |
Overfeat, Object Detection |
Deep Learning, Vision |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1312.6229.pdf |
Included |
|||
DeepLog: Anomaly Detection and Diagnosis from System Logs through Deep Learning |
ACM SIGSAC |
2017 |
DeepLog |
Anomaly Detection, Deep Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/deeplog.pdf |
Included |
|||
The expectation-maximization algorithm |
IEEE SPM |
1996 |
EM algorithm |
Machine Learning Basics |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/00543975.pdf |
Included |
|||
Data Clustering: A Review |
ACM Computing Surveys |
1999 |
Clustering Algorithms |
Clustering, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Data_Clustering_A_Review.pdf |
Included |
|||
A Comprehensive Survey on Graph Neural Networks |
IEEE TNNLS |
2020 |
GNN |
Graph, Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1901.00596.pdf |
Included |
|||
Learning Deep Architectures for AI |
Foundations and Trends in Machine Learning |
2009 |
Deep Learning in General |
Deep Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Bengio09_Learning_deep_architectures_for_AI.pdf |
Included |
|||
Deep learning for sentiment analysis: A survey |
2018 |
Sentiment Analysis |
NLP, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1801.07883.pdf |
Included |
||||
clValid: An R Package for Cluster Validation |
Journal of Staitiscal Software |
2008 |
Clustering Validity |
Clustering |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Brock08_clValid_an_R_package_for_cluster_validation.pdf |
Included |
|||
Process Mining Manifesto |
2011 |
Process Mining |
Data Mining |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Process_Mining_Manifesto.pdf, Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/ProcessMiningManifesto-Korean.pdf |
Included |
||||
An Introduction to Variable and Feature Selection |
Journal of Machine Learning Research |
2003 |
Variable Selection |
Dimensionality Reduction |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/AnIntroduction_to_Variable_and_Feature_Selection.pdf |
Included |
|||
Survey of Clustering Data Mining Techniques |
2006 |
Clustering Algorithms |
Clustering, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Survey_of_Clustering_Data_Mining_Techniques.pdf |
Included |
||||
A survey of sequential pattern mining |
DSPR |
2017 |
Sequential Pattern Mining |
Data Mining |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/dspr-paper5.pdf |
Included |
|||
A Tutorial on nu-Support Vector Machines |
2003 |
Kernel Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Nu_SVM_Tutorial.pdf |
Included |
|||||
An Introduction to Variational Autoencoders |
FTML |
2019 |
Variational Autoencoder |
Neural Network |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/1906.02691.pdf |
Included |
|||
Techniques of Cluster Algorithms in Data Mining |
Data Mining and Knowledge Discovery |
2002 |
Clustering Algorithms |
Clustering, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Techniques_of_Cluster_Algorithms_in_Data_Mining.pdf |
Included |
|||
Bagging Predictors |
Machine Learning |
1996 |
Bagging |
Ensemble Learning |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Breiman1996_Article_BaggingPredictors.pdf |
Included |
|||
From evolutionary computation to the evolution of things |
Nature |
2015 |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/EibenSmith15_NATURE_From_evolutionary_computation_to_the_evolution_of_things.pdf |
Included |
|||||
Probabilistic machine learning and artificial intelligence |
Nature |
2015 |
Artificial Intelligence |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/Ghahramani15_NATURE_Probabilistic_machine_learning_and_artificial_intelligence.pdf |
Included |
||||
Natural Language Processing (Almost) from Scratch |
Journal of Machine Learning Research |
2011 |
NLP |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/p2493-collobert.pdf |
Included |
||||
Anomaly Detection : A Survey |
ACM Computing Survey |
2009 |
Anomaly Detection |
Anomaly Detection, Survey |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/AnomalyDetection.pdf |
Included |
|||
The matrix calculus you need for deep learning |
2018 |
Matrix Calculus |
Machine Learning Basics |
Papers%20You%20Must%20Read%20(PYMR)%20715ea9e81933446cac682e8db6e45103/The_matrix_calculus_you_need_for_deep_learning.pdf |
Included |