Peter J. Haas

Artificial Intelligence · 2004–2011

A researcher in the Science corpus: 4 papers; trusts 5 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom Peter J. Haas trusts overall

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

  1. Sean P. Meyn
  2. Thomas Hofmann
  3. Peter Hall
  4. Ryan T. McDonald
  5. Daniel D. Lee
  6. Richard L. Tweedie

Who trusts Peter J. Haas overall

  1. Christopher C. Johnson
  2. Peva Blanchard
  3. Qirong Ho
  4. Eric P. Xing
  5. Henggang Cui
  6. Xixuan Feng

Papers from Peter J. Haas's perspective

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

  1. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
  2. Learning the parts of objects by non-negative matrix factorization
  3. Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models
  4. Parallelized Stochastic Gradient Descent
  5. Markov Chains and Stochastic Stability
  6. Stochastic Approximation and Recursive Algorithms and Applications
  7. Matrix Factorization Techniques for Recommender Systems
  8. Latent semantic models for collaborative filtering
  9. A Limited Memory Algorithm for Bound Constrained Optimization
  10. Google news personalization: scalable online collaborative filtering

Their papers