Tianlin Shi

1.2k citations
8 papers · 514 indexed · 1 hit paper · h-index 6
Topics
Sparse and Compressive Sensing Techniques (2 papers)Optimization and Search Problems (2 papers)Distributed Sensor Networks and Detection Algorithms (2 papers)
Partner nations
ChinaUnited States

In The Last Decade

Tianlin Shi

8 papers receiving 487 citations

Hit Papers

Adversarial Learning for Neural Dialogue Generation20172026202020232017100200300400

Peers

Tianlin Shi
Comparison fields: 5 of 65
  • Artificial Intelligence 399
  • Computer Vision and Pattern Recognition 202
  • Signal Processing 35
  • Information Systems 30
  • Control and Systems Engineering 17
Replace Biao Zhang with:
Biao Zhang China
Denny Britz United States
Chi-Min Chan China
Baosong Yang China
Zhixing Tan China
Denis Yarats Israel
Fangxiang Feng China
Rong Xiao China
Meiyu Liang China
S. Chitrakala India
Tianlin Shi relative to Biao Zhang China Biao Zhang's profile →
Citations per field
00.5×3.0×
Biao Zhang · 1×
Citations per year

Countries citing papers authored by Tianlin Shi

Since Specialization
Citations

This map shows the geographic impact of Tianlin Shi'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 Tianlin Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tianlin Shi more than expected).

Fields of papers citing papers by Tianlin Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tianlin Shi. 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 Tianlin Shi. The network helps show where Tianlin Shi may publish in the future.

Co-authorship network of co-authors of Tianlin Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Tianlin Shi. A scholar is included among the top collaborators of Tianlin Shi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tianlin Shi. Tianlin Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
#WorkIndexed citations
1
World of Bits: An Open-Domain Platform for Web-Based Agents
11
2
Adversarial Learning for Neural Dialogue Generationbreakdown →
467
3 2
4
Learning Where to Sample in Structured Prediction
7
5 6
6
Correlated compressive sensing for networked data
4
7 9
8
Online Bayesian Passive-Aggressive Learning
8

About Tianlin Shi

Tianlin Shi is a scholar working on Computer Networks and Communications, Artificial Intelligence and Statistics and Probability, having authored 8 papers that have together received 514 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (2 papers), Optimization and Search Problems (2 papers) and Distributed Sensor Networks and Detection Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (399 citations), Computer Vision and Pattern Recognition (202 citations) and Computational Mathematics (2 citations). Tianlin Shi has collaborated with scholars based in China and United States. Frequent co-authors include Jiwei Li, Will Monroe, Dan Jurafsky, Sébastien Jean, Alan Ritter, Percy Liang, Jun Zhu, Xiaolin Hu, Ming Liang and Jian Li. Their work appears in journals such as Journal of Machine Learning Research, Operations Research Letters and arXiv (Cornell University).

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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