awesome-ai-conferences's Introduction

Top AI Conferences Paper Statistics

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.

ICML 2020

Reference： Paper Digest

Author information statistics

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

keyword statistics

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

KDD 2020

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%

keyword statistics

Topic keyword statistics

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