Yingfei Wang

Optimization & Training · 2015

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 12 citations into it
• Artificial Intelligence — 8 citations into it; #29,775 of 35,345 by trust here, #31,361 by citations
• Statistics and Probability — 6 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Yingfei Wang trusts overall

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

1. Jerome H. Friedman
2. Leo Breiman
3. Martin Jaggi
4. Robert E. Schapire
5. Vladimir Koltchinskii
6. Robert Tibshirani
7. Yoav Freund
8. Llew Mason

Who trusts Yingfei Wang overall

1. Evgenii Egorov
2. Valentina Zantedeschi
3. Anna Kuzina
4. Francesco Locatello

Papers from Yingfei Wang's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. Greedy function approximation: A gradient boosting machine.
3. Special Invited Paper-Additive logistic regression: A statistical view of boosting
4. Prediction Games and Arcing Algorithms
5. A decision-theoretic generalization of on-line learning and an application to boosting
6. Boosting the margin: A new explanation for the effectiveness of voting methods
7. An algorithm for quadratic programming
8. Functional Gradient Techniques for Combining Hypotheses
9. Stochastic gradient boosting
10. Empirical margin distributions and bounding the generalization error of combined classifiers

Their papers

• Functional Frank-Wolfe Boosting for General Loss Functions (2015) — 21 citations