Bohdan M. Pavlyshenko

International Conference on Data Stream Mining & Processing · 2018

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Bohdan M. Pavlyshenko trusts overall

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

1. Jerome H. Friedman
2. John K. Kruschke
3. Tianqi Chen
4. Carlos Guestrin
5. David Hilton Wolpert

Papers from Bohdan M. Pavlyshenko's perspective

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

1. Greedy function approximation: A gradient boosting machine.
2. Stochastic gradient boosting
3. XGBoost: A Scalable Tree Boosting System
4. Regression Shrinkage and Selection via the Lasso
5. Random Forests
6. The Elements of Statistical Learning
7. ImageNet classification with deep convolutional neural networks
8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
9. Gradient-based learning applied to document recognition
10. Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan

Their papers

• Using Stacking Approaches for Machine Learning Models (2018) — 297 citations