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ORCIDRobert Tibshirani
Person information
- affiliation: Stanford University, USA
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2020 – today
- 2024
[j30]Ahmet Gorkem Er
, Daisy Yi Ding, Berrin Er, Mertcan Uzun, Mehmet Cakmak, Christoph Sadee, Gamze Durhan, Mustafa Nasuh Ozmen, Mine Durusu Tanriover, Arzu Topeli, Yesim Aydin Son, Robert Tibshirani, Serhat Unal, Olivier Gevaert:
Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study. npj Digit. Medicine 7(1) (2024)- [i7]Thomas Le Menestrel, Erin Craig, Robert Tibshirani, Trevor Hastie, Manuel A. Rivas:
Using Pre-training and Interaction Modeling for ancestry-specific disease prediction in UK Biobank. CoRR abs/2404.17626 (2024) - [i6]Erin Craig, Timothy Keyes, Jolanda Sarno, Maxim Zaslavsky, Garry Nolan, Kara Davis, Trevor Hastie, Robert Tibshirani:
MMIL: A novel algorithm for disease associated cell type discovery. CoRR abs/2406.08322 (2024) - 2023
- [c12]Daisy Yi Ding, Xiaotao Shen, Michael Snyder, Robert Tibshirani:
Semi-supervised Cooperative Learning for Multiomics Data Fusion. ML4MHD 2023: 54-63 - 2022
- [i5]Xuelin Yang, Louis Abraham, Sejin Kim, Petr Smirnov, Feng Ruan, Benjamin Haibe-Kains, Robert Tibshirani:
FastCPH: Efficient Survival Analysis for Neural Networks. CoRR abs/2208.09793 (2022) - 2021
- [j29]Vishnu Shankar, Robert Tibshirani, Richard N. Zare:
MassExplorer: a computational tool for analyzing desorption electrospray ionization mass spectrometry data. Bioinform. 37(20): 3688-3690 (2021) - [j28]Ruilin Li, Christopher Chang, Yosuke Tanigawa, Balasubramanian Narasimhan, Trevor Hastie, Robert Tibshirani, Manuel A. Rivas:
Fast numerical optimization for genome sequencing data in population biobanks. Bioinform. 37(22): 4148-4155 (2021) - [j27]Ruilin Li, Yosuke Tanigawa, Johanne M. Justesen, Jonathan Taylor, Trevor Hastie, Robert Tibshirani, Manuel A. Rivas:
Survival analysis on rare events using group-regularized multi-response Cox regression. Bioinform. 37(23): 4437-4443 (2021) - [j26]Ismael Lemhadri, Feng Ruan, Louis Abraham, Robert Tibshirani:
LassoNet: A Neural Network with Feature Sparsity. J. Mach. Learn. Res. 22: 127:1-127:29 (2021) - [j25]Avantika Lal, Keli Liu, Robert Tibshirani, Arend Sidow, Daniele Ramazzotti:
De novo mutational signature discovery in tumor genomes using SparseSignatures. PLoS Comput. Biol. 17(6) (2021) - [c11]Ismael Lemhadri, Feng Ruan, Robert Tibshirani:
LassoNet: Neural Networks with Feature Sparsity. AISTATS 2021: 10-18 - 2020
- [j24]Anthony Culos, Amy Tsai, Natalie Stanley, Martin Becker, Mohammad Sajjad Ghaemi, David Mcilwain, Ramin Fallahzadeh, Athena Tanada, Huda Nassar, Camilo Espinosa, Maria Xenochristou, Edward Ganio, Laura Peterson, Xiaoyuan Han, Ina A. Stelzer, Kazuo Ando, Dyani Gaudilliere, Thanaphong Phongpreecha, Ivana Maric, Alan L. Chang, Gary M. Shaw, David K. Stevenson, Sean Bendall, Kara L. Davis, Wendy J. Fantl, Garry P. Nolan, Trevor Hastie, Robert Tibshirani, Martin S. Angst, Brice Gaudilliere, Nima Aghaeepour:
Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions. Nat. Mach. Intell. 2(10): 619-628 (2020) - [i4]J. Kenneth Tay, Nima Aghaeepour, Trevor Hastie, Robert Tibshirani:
Feature-weighted elastic net: using "features of features" for better prediction. CoRR abs/2006.01395 (2020)
2010 – 2019
- 2019
- [j23]Mohammad Sajjad Ghaemi, Daniel B. DiGiulio, Kévin Contrepois, Benjamin J. Callahan, Thuy T. M. Ngo, Brittany Lee-McMullen, Benoit Lehallier, Anna Robaczewska, David Mcilwain, Yael Rosenberg-Hasson, Ronald J. Wong, Cecele Quaintance, Anthony Culos, Natalie Stanley, Athena Tanada, Amy Tsai, Dyani Gaudilliere, Edward Ganio, Xiaoyuan Han, Kazuo Ando, Leslie McNeil, Martha Tingle, Paul H. Wise, Ivana Maric, Marina Sirota, Tony Wyss-Coray, Virginia D. Winn, Maurice L. Druzin, Ronald Gibbs, Gary L. Darmstadt, David B. Lewis, Vahid Partovi Nia, Bruno Agard, Robert Tibshirani, Garry P. Nolan, Michael P. Snyder, David A. Relman, Stephen R. Quake, Gary M. Shaw, David K. Stevenson, Martin S. Angst, Brice Gaudilliere, Nima Aghaeepour:
Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy. Bioinform. 35(1): 95-103 (2019) - [i3]Jonathan Johannemann, Robert Tibshirani:
Spectral Overlap and a Comparison of Parameter-Free, Dimensionality Reduction Quality Metrics. CoRR abs/1907.01974 (2019) - [i2]Ismael Lemhadri, Feng Ruan, Robert Tibshirani:
A neural network with feature sparsity. CoRR abs/1907.12207 (2019) - 2017
- [j22]William Yuan, Dadi Jiang, Dhanya K. Nambiar, Lydia P. Liew, Michael P. Hay, Joshua Bloomstein, Peter Lu, Brandon Turner, Quynh-Thu Le, Robert Tibshirani, Purvesh Khatri, Mark G. Moloney, Albert C. Koong:
Chemical Space Mimicry for Drug Discovery. J. Chem. Inf. Model. 57(4): 875-882 (2017) - 2016
- [j21]Samuel M. Gross, Robert Tibshirani:
Data Shared Lasso: A novel tool to discover uplift. Comput. Stat. Data Anal. 101: 226-235 (2016) - [j20]Robert Tibshirani, Xiaotong Suo:
An Ordered Lasso and Sparse Time-Lagged Regression. Technometrics 58(4) (2016) - [c10]Mohammad Shahrokh Esfahani, Aaron M. Newman, Florian Scherer, Robert Tibshirani, Maximilian Diehn, Ash A. Alizadeh:
Noninvasive Cancer Classification Using Diverse Genomic Features in Circulating Tumor DNA. BCB 2016: 516 - 2014
- [j19]Max Grazier G'Sell, Shai S. Shen-Orr, Robert Tibshirani:
Sensitivity analysis for inference with partially identifiable covariance matrices. Comput. Stat. 29(3): 529-546 (2014) - 2013
- [j18]Daniela M. Witten, Robert Tibshirani:
Scientific research in the age of omics: the good, the bad, and the sloppy. J. Am. Medical Informatics Assoc. 20(1): 125-127 (2013) - [i1]Nadine Hussami, Robert Tibshirani:
A Component Lasso. CoRR abs/1311.4472 (2013) - 2011
- [j17]Daniela M. Witten, Robert Tibshirani:
Supervised multidimensional scaling for visualization, classification, and bipartite ranking. Comput. Stat. Data Anal. 55(1): 789-801 (2011) - [j16]Ryan J. Tibshirani, Holger Höfling, Robert Tibshirani:
Nearly-Isotonic Regression. Technometrics 53(1): 54-61 (2011) - 2010
- [j15]Keyan Salari, Robert Tibshirani, Jonathan R. Pollack:
DR-Integrator: a new analytic tool for integrating DNA copy number and gene expression data. Bioinform. 26(3): 414-416 (2010) - [j14]Rahul Mazumder, Trevor Hastie, Robert Tibshirani:
Spectral Regularization Algorithms for Learning Large Incomplete Matrices. J. Mach. Learn. Res. 11: 2287-2322 (2010)
2000 – 2009
- 2009
- [b3]Trevor Hastie, Robert Tibshirani, Jerome H. Friedman:
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition. Springer Series in Statistics, Springer 2009, ISBN 9780387848570, pp. I-XXII, 1-745 - [j13]Holger Höfling, Robert Tibshirani:
Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods. J. Mach. Learn. Res. 10: 883-906 (2009) - 2008
- [c9]Trevor Hastie, Jerome H. Friedman, Robert Tibshirani:
Regularization paths and coordinate descent. KDD 2008: 3 - 2007
- [j12]Monica Nicolau, Robert Tibshirani, Anne-Lise Børresen-Dale, Stefanie S. Jeffrey:
Disease-specific genomic analysis: identifying the signature of pathologic biology. Bioinform. 23(8): 957-965 (2007) - [j11]Robert Tibshirani, Trevor Hastie:
Margin Trees for High-dimensional Classification. J. Mach. Learn. Res. 8: 637-652 (2007) - 2006
- [j10]Robert Tibshirani:
A simple method for assessing sample sizes in microarray experiments. BMC Bioinform. 7: 106 (2006) - 2005
- [p1]Robert Tibshirani:
43. Who Is the Fastest Man in the World? Anthology of Statistics in Sports 2005: 311-316 - 2004
- [j9]Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan, Scott G. Soltys, Gongyi Shi, Albert C. Koong, Quynh-Thu Le:
Sample classification from protein mass spectrometry, by 'peak probability contrasts'. Bioinform. 20(17): 3034-3044 (2004) - [j8]Kamesh Munagala, Robert Tibshirani, Patrick O. Brown:
Cancer characterization and feature set extraction by discriminative margin clustering. BMC Bioinform. 5: 21 (2004) - [j7]Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu:
The Entire Regularization Path for the Support Vector Machine. J. Mach. Learn. Res. 5: 1391-1415 (2004) - [c8]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 - [c7]Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu:
The Entire Regularization Path for the Support Vector Machine. NIPS 2004: 561-568 - 2003
- [j6]Trevor Hastie, Robert Tibshirani, Jerome H. Friedman:
Note on "Comparison of Model Selection for Regression" by Vladimir Cherkassky and Yunqian Ma. Neural Comput. 15(7): 1477-1480 (2003) - [j5]Eric Bair, Robert Tibshirani:
Machine learning methods applied to DNA microarray data can improve the diagnosis of cancer. SIGKDD Explor. 5(2): 48-55 (2003) - [c6]Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibshirani:
1-norm Support Vector Machines. NIPS 2003: 49-56 - 2002
- [c5]Trevor Hastie, Robert Tibshirani, Balasubramanian Narasimhan, Gilbert Chu:
Supervised Learning from Microarray Data. COMPSTAT 2002: 67-77 - [c4]Trevor Hastie, Robert Tibshirani:
Independent Components Analysis through Product Density Estimation. NIPS 2002: 649-656 - 2001
- [b2]Trevor Hastie, Jerome H. Friedman, Robert Tibshirani:
The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer Series in Statistics, Springer 2001, ISBN 978-1-4899-0519-2, pp. 1-536 - [j4]Olga G. Troyanskaya, Michael N. Cantor, Gavin Sherlock, Patrick O. Brown, Trevor Hastie, Robert Tibshirani, David Botstein, Russ B. Altman:
Missing value estimation methods for DNA microarrays. Bioinform. 17(6): 520-525 (2001)
1990 – 1999
- 1998
- [j3]Robert Tibshirani, Geoffrey E. Hinton:
Coaching variables for regression and classification. Stat. Comput. 8(1): 25-33 (1998) - 1997
- [c3]Trevor Hastie, Robert Tibshirani:
Classification by Pairwise Coupling. NIPS 1997: 507-513 - 1996
- [j2]Robert Tibshirani:
A Comparison of Some Error Estimates for Neural Network Models. Neural Comput. 8(1): 152-163 (1996) - [j1]Trevor Hastie, Robert Tibshirani:
Discriminant Adaptive Nearest Neighbor Classification. IEEE Trans. Pattern Anal. Mach. Intell. 18(6): 607-616 (1996) - 1995
- [c2]Trevor Hastie, Robert Tibshirani:
Discriminant Adaptive Nearest Neighbor Classification. KDD 1995: 142-149 - [c1]Trevor Hastie, Robert Tibshirani:
Discriminant Adaptive Nearest Neighbor Classification and Regression. NIPS 1995: 409-415 - 1993
- [b1]Bradley Efron, Robert Tibshirani:
An Introduction to the Bootstrap. Springer 1993, ISBN 978-1-4899-4541-9, pp. 1-397
Coauthor Index
aka: Trevor Hastie
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