Jim McFadden

2003

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Whom Jim McFadden trusts overall

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

1. Kevin Leyton-Brown

Who trusts Jim McFadden overall

1. Holger H. Hoos
2. K. Smith‐Miles

Papers from Jim McFadden's perspective

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

1. The Strength of Weak Learnability
2. An algorithm for the selection problem
3. Towards a universal test suite for combinatorial auction algorithms (ACM Conference on Economics and Computation)
4. Sequential Monte Carlo Methods in Practice
5. Sequential Monte Carlo Methods in Practice
6. Learning the Empirical Hardness of Optimization Problems: The Case of Combinatorial Auctions
7. Algorithm portfolios (Artificial Intelligence)
8. A portfolio approach to algorithm select
9. Learning Multiple Layers of Features from Tiny Images
10. A Fast Learning Algorithm for Deep Belief Nets

Their papers

• Boosting as a Metaphor for Algorithm Design (2003) — 80 citations