This repo organizes various top conferences related to AI and data science to provide statistics on the keywords, themes, and author information of papers accepted by each conference.
Reference: Paper Digest
Top 10 authors:
author | num_papers | University |
---|---|---|
Masashi Sugiyama | 11 | University of Tokyo |
Michael Jordan | 8 | UC Berkeley |
Michal Valko | 8 | DeepMind & Inria & ENS |
Dale Schuurmans | 8 | Google Brain & U of Alberta |
Zhaoran Wang | 7 | Northwestern U |
Gang Niu | 7 | RIKEN AIP |
Mihaela van der Schaar | 7 | University of Cambridge |
Percy Liang | 7 | Stanford |
Tommi Jaakkola | 7 | MIT |
Steven Wu | 6 | U of Minnesota |
topic | num_papers |
---|---|
reinforcement learning | 59 |
graph | 58 |
GAN | 17 |
private | 14 |
unsupervised | 11 |
uncertainty | 11 |
multi-task | 8 |
generative adversarial | 8 |
GANs | 7 |
online learning | 7 |
semi-supervised | 7 |
Differential Privacy | 6 |
few-shot | 6 |
transfer learning | 5 |
Federated | 5 |
Federated learning | 5 |
convolutional neural networks | 4 |
Q-learning | 4 |
time series | 4 |
CNN | 4 |
generative adversarial | 4 |
interpretability | 2 |
Knowledge Distillation | 1 |
real time | 1 |
GNN | 1 |
real-time | 1 |
summary:
- Total num (RT+ADS), Research Track, and Applied Data Science (ADS) track of paper in KDD 2020 is **338 217 121 **
- Total number of submissions: 2035 (the highest in history, over 13% more than the second highest one)
- Research track(long paper): 1279 submissions, 216 accepted, 216 / 1279 = 16.9%
topic | num_papers |
---|---|
graph | 74 |
convolutional neural networks | 6 |
unsupervised | 6 |
generative adversarial | 6 |
reinforcement learning | 6 |
time series | 5 |
semi-supervised | 5 |
real-time | 5 |
GAN | 4 |
GNN | 4 |
multi-task | 4 |
GCN | 3 |
meta-learning | 3 |
Federated | 2 |
privacy | 2 |
private | 1 |
interpretability | 1 |
Knowledge Distillation | 1 |
co-training | 1 |
CNN | 1 |
GANs | 1 |
transfer learning | 1 |