Robust Loss Functions
Robust Loss Functions is a class of loss functions in statistical learning and optimization that belongs to the broader category of objective functions used for model training, distinguished by its reduced sensitivity to outliers through the incorporation of mechanisms that downweight or bound the influence of large residuals.
778
Publications
55.5K
Citations
2K
Authors
692
Institutions
Publications per year
2017–2026
480
Parents
778
Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
Wei‐Sheng Lai, Jia‐Bin Huang, Narendra Ahuja et al. · 2017 · 3K citations
BOOSTED TREES FOR ECOLOGICAL MODELING AND PREDICTION
Glenn De’ath · Ecology · 2007 · 1.3K citations
Computing, Biostatistics, Ecology +13
1–5 of 778
2K
10
h-index
8
h-index
7
h-index
6
h-index
6
h-index
1–5 of 2K
692

Chinese Academy of Sciences
Beijing, China
19 h-index
57 publications
4.5K citations

Xi'an Jiaotong University
Xi'an, China
14 h-index
38 publications
3.1K citations
University of Chinese Academy of Sciences
Beijing, China
14 h-index
30 publications
1.4K citations
Tsinghua University
Beijing, China
13 h-index
40 publications
2.4K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
12 h-index
22 publications
952 citations
China Agricultural University
Beijing, China
12 h-index
32 publications
807 citations

Northwestern Polytechnical University
Xi'an, China
12 h-index
24 publications
1.5K citations
Nanjing University of Science and Technology
Nanjing, China
11 h-index
28 publications
1.1K citations
1–8 of 692
Repository · 117 publications · 11.2K citations
42
h-index
TPAMI · 17 publications · 2K citations
17
h-index
Conference · 17 publications · 1.7K citations
16
h-index
14 publications · 1.3K citations
14
h-index
12 publications · 739 citations
12
h-index
1–5