Umair Ahmed

Statistics and Probability · with Anwar · 2019

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Umair Ahmed trusts overall

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

  1. Leo Breiman
  2. Jerome H. Friedman
  3. Harry Zhang
  4. Frauke Günther
  5. Hui Zou
  6. Cyril Goutte
  7. Andy Liaw
  8. Simon Tong
  9. Cort J. Willmott
  10. David W. Hosmer Jr.

Papers from Umair Ahmed's perspective

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

  1. Regression Shrinkage and Selection via the Lasso
  2. Bagging Predictors
  3. Stochastic gradient boosting
  4. Ridge Regression: Biased Estimation for Nonorthogonal Problems
  5. Applied Logistic Regression: Hosmer/Applied Logistic Regression
  6. Large-Scale Machine Learning with Stochastic Gradient Descent
  7. Support Vector Machine Active Learning with Applications to Text Classification
  8. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance
  9. The Nature of Statistical Learning Theory
  10. Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation (Australian Conference on Artificial Intelligence)

Their papers