C. Volinsky
Information Systems · 1999–2016
A researcher in the Science corpus: 9 papers; trusts 22 researchers and is trusted by 430 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 26 citations into it; #16 of 8,771 by trust here, #30 by citations
- Artificial Intelligence — 23 citations into it
- Recommender Systems — 17 citations into it; #19 of 233 by trust here, #18 by citations
- Statistics and Probability — 16 citations into it
- Probabilistic & Bayesian Methods — 15 citations into it
- Management Science and Operations Research — 14 citations into it; #295 of 11,946 by trust here, #321 by citations
- Computer Vision and Pattern Recognition — 12 citations into it; #2,343 of 21,575 by trust here, #1,370 by citations
- Marketing — 7 citations into it; #5 of 6,289 by trust here, #15 by citations
Whom C. Volinsky trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Eric R. Ziegel
- Thomas Hofmann
- Yehuda Koren
- Robert M. Bell
- Larry A. Wasserman
- Badrul Munir Sarwar
- Anthony B. Atkinson
- Richard E. Neapolitan
- Arkadiusz Paterek
- J. Konstan
Who trusts C. Volinsky overall
- Julian McAuley
- Xiangnan He
- Yehuda Koren
- Hao Wang
- Harald Steck
- Ruining He
- Yongfeng Zhang
- Charu C. Aggarwal
- Yue Shi
- Dawen Liang
Papers from C. Volinsky's perspective
Ordered by how strongly the researchers C. Volinsky trusts endorse each paper. Same corpus, a different order for every researcher.
- GroupLens: applying collaborative filtering to Usenet news
- Using collaborative filtering to weave an information tapestry
- Generalized Linear Models
- Estimating the Dimension of a Model
- Application of Dimensionality Reduction in Recommender System - A Case Study
- The Anatomy of a Large-Scale Hypertextual Web Search Engine
- Explaining collaborative filtering recommendations
- Latent semantic models for collaborative filtering
- Implicit Feedback for Recommender Systems
- ImageNet classification with deep convolutional neural networks
Their papers
- Matrix Factorization Techniques for Recommender Systems (2009) — 10,960 citations
- Collaborative Filtering for Implicit Feedback Datasets (2008) — 3,563 citations
- Modeling relationships at multiple scales to improve accuracy of large recommender systems (2007) — 411 citations
- Bayesian Model Averaging: A Tutorial (2016) — 3,317 citations
- All Together Now: A Perspective on the Netflix Prize (2010) — 88 citations
- The BellKor solution to the Netflix Prize (2007) — 239 citations
- Network-Based Marketing: Identifying Likely Adopters Via Consumer Networks (2006) — 618 citations
- Correction to: ``Bayesian model averaging: a tutorial'' [Statist. Sci. 14 (1999), no. 4, 382--417; MR 2001a:62033] (2000) — 117 citations
- Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors (1999)