Koby Bibas

2019

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

Whom Koby Bibas trusts overall

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

1. Vladimir Naumovich Vapnik
2. David Ruppert
3. Eduardo Sontag

Papers from Koby Bibas's perspective

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

1. Ridge Regression: Biased Estimation for Nonorthogonal Problems
2. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
3. Principles of Risk Minimization for Learning Theory
4. An Introduction to Statistical Learning
5. VC dimension of neural networks
6. Estimating the Dimension of a Model
7. Subset Selection in Regression
8. Information Theory and an Extension of the Maximum Likelihood Principle
9. Statistical predictor identification
10. A training algorithm for optimal margin classifiers

Their papers

• A New Look at an Old Problem: A Universal Learning Approach to Linear Regression (2019) — 36 citations