Robert Tibshirani

Daniela M. Witten, Robert Tibshirani: Scientific research in the age of omics: the good, the bad, and the sloppy. JAMIA 20(1): 125-127 (2013)

Daniela M. Witten, Robert Tibshirani: Supervised multidimensional scaling for visualization, classification, and bipartite ranking. Computational Statistics & Data Analysis 55(1): 789-801 (2011)

Keyan Salari, Robert Tibshirani, Jonathan R. Pollack: DR-Integrator: a new analytic tool for integrating DNA copy number and gene expression data. Bioinformatics 26(3): 414-416 (2010)

Rahul Mazumder, Trevor Hastie, Robert Tibshirani: Spectral Regularization Algorithms for Learning Large Incomplete Matrices. Journal of Machine Learning Research 11: 2287-2322 (2010)

Holger Höfling, Robert Tibshirani: Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods. Journal of Machine Learning Research 10: 883-906 (2009)

Trevor Hastie, Jerome Friedman, Robert Tibshirani: Regularization paths and coordinate descent. KDD 2008: 3

Monica Nicolau, Robert Tibshirani, Anne-Lise Børresen-Dale, Stefanie S. Jeffrey: Disease-specific genomic analysis: identifying the signature of pathologic biology. Bioinformatics 23(8): 957-965 (2007)

Robert Tibshirani, Trevor Hastie: Margin Trees for High-dimensional Classification. Journal of Machine Learning Research 8: 637-652 (2007)

Robert Tibshirani: A simple method for assessing sample sizes in microarray experiments. BMC Bioinformatics 7: 106 (2006)

Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan, Scott Soltys, Gongyi Shi, Albert Koong, Quynh-Thu Le: Sample classification from protein mass spectrometry, by 'peak probability contrasts'. Bioinformatics 20(17): 3034-3044 (2004)

Kamesh Munagala, Robert Tibshirani, Patrick O. Brown: Cancer characterization and feature set extraction by discriminative margin clustering. BMC Bioinformatics 5: 21 (2004)

Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu: The Entire Regularization Path for the Support Vector Machine. Journal of Machine Learning Research 5: 1391-1415 (2004)

Pei Wang, Young Kim, Jonathan R. Pollack, Robert Tibshirani: Boosted PRIM with Application to Searching for Oncogenic Pathway of Lung Cancer. CSB 2004: 604-609

Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu: The Entire Regularization Path for the Support Vector Machine. NIPS 2004

Trevor Hastie, Robert Tibshirani, Jerome Friedman: Note on "Comparison of Model Selection for Regression" by Vladimir Cherkassky and Yunqian Ma. Neural Computation 15(7): 1477-1480 (2003)

Eric Bair, Robert Tibshirani: Machine learning methods applied to DNA microarray data can improve the diagnosis of cancer. SIGKDD Explorations 5(2): 48-55 (2003)

Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibshirani: 1-norm Support Vector Machines. NIPS 2003

Trevor Hastie, Robert Tibshirani: Independent Components Analysis through Product Density Estimation. NIPS 2002: 649-656

Olga G. Troyanskaya, Michael Cantor, Gavin Sherlock, Patrick O. Brown, Trevor Hastie, Robert Tibshirani, David Botstein, Russ B. Altman: Missing value estimation methods for DNA microarrays. Bioinformatics 17(6): 520-525 (2001)

Trevor Hastie, Robert Tibshirani: Classification by Pairwise Coupling. NIPS 1997

Trevor Hastie, Robert Tibshirani: Discriminant Adaptive Nearest Neighbor Classification. IEEE Trans. Pattern Anal. Mach. Intell. 18(6): 607-616 (1996)

Trevor Hastie, Robert Tibshirani: Discriminant Adaptive Nearest Neighbor Classification. KDD 1995: 142-149

Trevor Hastie, Robert Tibshirani: Discriminant Adaptive Nearest Neighbor Classification and Regression. NIPS 1995: 409-415