马上召开的ICML2012

tangzk

International Conference on Machine Learning 2012（ICML2012）马上就要召开了，录取的论文列表（Accepted Papers）：http://icml.cc/2012/papers/
另外博客Machine Learning(Theory)作了个统计，其中包括各个研究分支的投稿/录取比例，研究热度等信息，原文见：http://hunch.net/?p=2517
统计如下：

18/66 = 0.27	in (0.18,0.36)	Reinforcement Learning
10/52 = 0.19	in (0.17,0.37)	Supervised Learning
9/51 = 0.18	not in (0.18, 0.37)	Clustering
12/46 = 0.26	in (0.17, 0.37)	Kernel Methods
11/40 = 0.28	in (0.15, 0.4)	Optimization Algorithms
8/33 = 0.24	in (0.15, 0.39)	Learning Theory
14/33 = 0.42	not in (0.15, 0.39)	Graphical Models
10/32 = 0.31	in (0.15, 0.41)	Applications (+5 invited)
8/29 = 0.28	in (0.14, 0.41])	Probabilistic Models
13/29 = 0.45	not in (0.14, 0.41)	NN & Deep Learning
8/26 = 0.31	in (0.12, 0.42)	Transfer and Multi-Task Learning
13/25 = 0.52	not in (0.12, 0.44)	Online Learning
5/25 = 0.20	in (0.12, 0.44)	Active Learning
6/22 = 0.27	in (0.14, 0.41)	Semi-Supervised Learning
7/20 = 0.35	in (0.1, 0.45)	Statistical Methods
4/20 = 0.20	in (0.1, 0.45)	Sparsity and Compressed Sensing
1/19 = 0.05	not in (0.11, 0.42)	Ensemble Methods
5/18 = 0.28	in (0.11, 0.44)	Structured Output Prediction
4/18 = 0.22	in (0.11, 0.44)	Recommendation and Matrix Factorization
7/18 = 0.39	in (0.11, 0.44)	Latent-Variable Models and Topic Models
1/17 = 0.06	not in (0.12, 0.47)	Graph-Based Learning Methods
5/16 = 0.31	in (0.13, 0.44)	Nonparametric Bayesian Inference
3/15 = 0.20	in (0.7, 0.47)	Unsupervised Learning and Outlier Detection
7/12 = 0.58	not in (0.08, 0.50)	Gaussian Processes
5/11 = 0.45	not in (0.09, 0.45)	Ranking and Preference Learning
2/11 = 0.18	in (0.09, 0.45)	Large-Scale Learning
0/9 = 0.00	in [0, 0.56)	Vision
3/9 = 0.33	in [0, 0.56)	Social Network Analysis
0/9 = 0.00	in [0, 0.56)	Multi-agent & Cooperative Learning
2/9 = 0.22	in [0, 0.56)	Manifold Learning
4/8 = 0.50	not in [0, 0.5)	Time-Series Analysis
2/8 = 0.25	in [0, 0.5]	Large-Margin Methods
2/8 = 0.25	in [0, 0.5]	Cost Sensitive Learning
2/7 = 0.29	in [0, 0.57)	Recommender Systems
3/7 = 0.43	in [0, 0.57)	Privacy, Anonymity, and Security
0/7 = 0.00	in [0, 0.57)	Neural Networks
0/7 = 0.00	in [0, 0.57)	Empirical Insights
0/7 = 0.00	in [0, 0.57)	Bioinformatics
1/6 = 0.17	in [0, 0.5)	Information Retrieval
2/6 = 0.33	in [0, 0.5)	Evaluation Methodology

Update: See Brendan’s graph for a visualization.

I usually find these numbers hard to interpret. At the grossest level, all areas have significant selection. At a finer level, one way to add further interpretation is to pretend that the acceptance rate of all papers is 0.27, then compute a 5% lower tail and a 5% upper tail. With 40 categories, we expect to have about 4 violations of tail inequalities. Instead, we have 9, so there is some evidence that individual areas are particularly hot or cold. In particular, the hot topics are Graphical models, Neural Networks and Deep Learning, Online Learning, Gaussian Processes, Ranking and Preference Learning, and Time Series Analysis. The cold topics are Clustering, Ensemble Methods, and Graph-Based Learning Methods.

tangzk

建议开下论坛的html代码编辑功能吧，我实在无法忍受这表格格式成为这样子的了。

xmubingo

tangzk 发表于 2012-6-8 11:49
建议开下论坛的html代码编辑功能吧，我实在无法忍受这表格格式成为这样子的了。

找 @cwc，叫他开。

cwc

xmubingo 发表于 2012-6-8 11:55
找 @cwc，叫他开。

开启html功能具有比较大的安全隐患，还是不建议开启哦。