Jing Bai

Artificial Intelligence · with Chang · 2009–2010

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jing Bai trusts overall

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

  1. Jerome H. Friedman
  2. Thorsten Joachims
  3. Kalervo Järvelin
  4. Jaana Kekäläinen
  5. R. Caruana
  6. Jonathan Baxter

Who trusts Jing Bai overall

  1. Yu Zhang
  2. Qiang Yang

Papers from Jing Bai's perspective

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

  1. Greedy function approximation: A gradient boosting machine.
  2. Multitask Learning
  3. Stochastic gradient boosting
  4. Learning to rank using gradient descent
  5. Optimizing search engines using clickthrough data
  6. Cumulated gain-based evaluation of IR techniques
  7. Task Clustering and Gating for Bayesian Multitask Learning
  8. Bursty and Hierarchical Structure in Streams (Data mining and knowledge discovery)
  9. Learning Gaussian processes from multiple tasks
  10. A Bayesian/Information Theoretic Model of Learning to Learn via Multiple Task Sampling

Their papers