Taiyao Wang

Artificial Intelligence · 2016–2018

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it

Whom Taiyao Wang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Trevor J. Hastie
2. Vladimir Naumovich Vapni

Papers from Taiyao Wang's perspective

Ordered by how strongly the researchers Taiyao Wang trusts endorse each paper. Same corpus, a different order for every researcher.

1. The Nature of Statistical Learning Theory
2. Support-Vector Networks
3. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
4. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
5. Random Forests
6. Bayesian t tests for accepting and rejecting the null hypothesis (Psychonomic Bulletin & Review)
7. Boosting Algorithms as Gradient Descent
8. Introduction to Statistical Learning Theory
9. A machine learning-based framework to identify type 2 diabetes through electronic health records
10. Points of Significance: Classification evaluation

Their papers

• Predicting diabetes-related hospitalizations based on electronic health records (2018) — 35 citations
• A joint sparse clustering and classification approach with applications to hospitalization prediction (2016) — 9 citations