Po‐Ling Loh

2.0k citations
36 papers · 726 · h-index 12

Impact in

Papers in

Po‐Ling Loh

35 papers receiving 697 citations

Peers

Po‐Ling Loh
Comparison fields: 5 of 103
  • Statistics and Probability 270
  • Computational Mechanics 172
  • Artificial Intelligence 218
  • Computational Mathematics 4
  • Health Informatics 8
Replace Yuling Jiao with:
Yuling Jiao China
Eunho Yang South Korea
Don Hush United States
Shuheng Zhou United States
Cun-Hui Zhang United States
Heiko Strathmann United Kingdom
Zhen Xiang United States
Adel Javanmard United States
G. Koch Italy
Jiantao Jiao United States
Po‐Ling Loh relative to Yuling Jiao China Yuling Jiao's profile →
Citations per field
00.5×
Yuling Jiao · 1×
Citations per year

Countries citing papers authored by Po‐Ling Loh

Since Specialization
Citations

This map shows the geographic impact of Po‐Ling Loh's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Po‐Ling Loh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Po‐Ling Loh more than expected).

Fields of papers citing papers by Po‐Ling Loh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Po‐Ling Loh. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Po‐Ling Loh. The network helps show where Po‐Ling Loh may publish in the future.

Co-authors

The 25 scholars most cited alongside Po‐Ling Loh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Po‐Ling Loh Line = papers co-authored together Po‐Ling Loh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012232
2
Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima
2013122
3 2017118
4 202032
5 201125
6 202023
7 201622
8 201817
9 201214
10 201614
11 202112
12 200911
13 201710
14 20176
15 20126
16 20236
17 20155
18 20235
19
Adversarial Risk Bounds for Binary Classification via Function Transformation.
20185
20 20244

About Po‐Ling Loh

Po‐Ling Loh is a scholar working on Artificial Intelligence, Statistics and Probability, Computer Networks and Communications, Computational Mechanics and Statistical and Nonlinear Physics, having authored 36 papers that have together received 726 indexed citations. Recurring topics across this work include Statistical Methods and Inference (11 papers), Sparse and Compressive Sensing Techniques (8 papers), Distributed Sensor Networks and Detection Algorithms (6 papers), Complex Network Analysis Techniques (5 papers), Adversarial Robustness in Machine Learning (4 papers), Advanced Statistical Methods and Models (4 papers), Machine Learning and Algorithms (3 papers) and Advanced Statistical Process Monitoring (3 papers). The work is most often cited by research in Statistics and Probability (270 citations), Computational Mechanics (172 citations), Artificial Intelligence (218 citations), Computational Mathematics (4 citations) and Health Informatics (8 citations). Po‐Ling Loh has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Martin J. Wainwright, Varun Jog, Jina Ko, Konrad P. Körding, Steven N. Baldassano, David Issadore, Brian Litt, Min Xu, Todd R. Allen and Kaibo Liu. Their work appears in journals such as The Annals of Statistics, Nuclear Engineering and Design, Information and Inference A Journal of the IMA, IEEE Transactions on Network Science and Engineering and IEEE Transactions on Information Theory.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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