• 2302 Citations
  • 25 h-Index
20042020
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Fingerprint Dive into the research topics where Ping Li is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Random Projection Mathematics
Recovery Engineering & Materials Science
Compressed sensing Engineering & Materials Science
Experiments Engineering & Materials Science
Learning systems Engineering & Materials Science
Compressed Sensing Mathematics
Glossaries Engineering & Materials Science
Dimension Reduction Mathematics

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2013 2016

Data reduction
Sampling
Data visualization
Search engines
NASA
Data reduction
Sampling
Data visualization
Search engines
NASA
Statistical methods
Statistics
Linear algebra
Curricula
Learning systems
Statistical methods
Statistics
Linear algebra
Curricula
Learning systems
Factorization
Knowledge acquisition
Distance education
Singular value decomposition
Computer vision

Research Output 2004 2020

Covariance matrix
High-dimensional
Two-sample Test
Sample Covariance Matrix
Significance level

AIBox: CTR prediction model training on a single node

Li, P., Nov 3 2019, CIKM 2019 - Proceedings of the 28th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, p. 319-328 10 p. (International Conference on Information and Knowledge Management, Proceedings).

Rutgers, The State University

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
Node
Prediction model
Click-through rate
Prediction
Costs
Linear regression
Labels
Recovery
Hardness

Coreference aware representation learning for neural named entity recognition

Li, P., Jan 1 2019, Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. Kraus, S. (ed.). International Joint Conferences on Artificial Intelligence, p. 4946-4953 8 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2019-August).

Rutgers, The State University

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Neural networks
Gold

Deep skip-gram networks for text classification

Li, P., Jan 1 2019, SIAM International Conference on Data Mining, SDM 2019. Society for Industrial and Applied Mathematics Publications, p. 145-153 9 p. (SIAM International Conference on Data Mining, SDM 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Recurrent neural networks
Convolution
Tuning
Processing
Experiments