Robert Tibshirani

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 20

Top Topics

Mass Spectrometry

Covariance Matrices

Survival Analysis

Top Venues

Publications

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 (2024)
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)
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 (2024)
Daisy Yi Ding, Xiaotao Shen, Michael Snyder, Robert Tibshirani
Semi-supervised Cooperative Learning for Multiomics Data Fusion. ML4MHD (2023)
Xuelin Yang, Louis Abraham, Sejin Kim, Petr Smirnov, Feng Ruan, Benjamin Haibe-Kains, Robert Tibshirani
FastCPH: Efficient Survival Analysis for Neural Networks. CoRR (2022)
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) (2021)
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) (2021)
Ismael Lemhadri, Feng Ruan, Robert Tibshirani
LassoNet: Neural Networks with Feature Sparsity. AISTATS (2021)
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)
Ismael Lemhadri, Feng Ruan, Louis Abraham, Robert Tibshirani
LassoNet: A Neural Network with Feature Sparsity. J. Mach. Learn. Res. 22 (2021)
Vishnu Shankar, Robert Tibshirani, Richard N. Zare
MassExplorer: a computational tool for analyzing desorption electrospray ionization mass spectrometry data. Bioinform. 37 (20) (2021)
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) (2020)
J. Kenneth Tay, Nima Aghaeepour, Trevor Hastie, Robert Tibshirani
Feature-weighted elastic net: using "features of features" for better prediction. CoRR (2020)
Jonathan Johannemann, Robert Tibshirani
Spectral Overlap and a Comparison of Parameter-Free, Dimensionality Reduction Quality Metrics. CoRR (2019)
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) (2019)
Ismael Lemhadri, Feng Ruan, Robert Tibshirani
A neural network with feature sparsity. CoRR (2019)
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) (2017)
Samuel M. Gross, Robert Tibshirani
Data Shared Lasso: A novel tool to discover uplift. Comput. Stat. Data Anal. 101 (2016)
Robert Tibshirani, Xiaotong Suo
An Ordered Lasso and Sparse Time-Lagged Regression. Technometrics 58 (4) (2016)
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)
Max Grazier G'Sell, Shai S. Shen-Orr, Robert Tibshirani
Sensitivity analysis for inference with partially identifiable covariance matrices. Comput. Stat. 29 (3) (2014)
Nadine Hussami, Robert Tibshirani
A Component Lasso. CoRR (2013)
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) (2013)
Ryan J. Tibshirani, Holger Höfling, Robert Tibshirani
Nearly-Isotonic Regression. Technometrics 53 (1) (2011)
Daniela M. Witten, Robert Tibshirani
Supervised multidimensional scaling for visualization, classification, and bipartite ranking. Comput. Stat. Data Anal. 55 (1) (2011)
Rahul Mazumder, Trevor Hastie, Robert Tibshirani
Spectral Regularization Algorithms for Learning Large Incomplete Matrices. J. Mach. Learn. Res. 11 (2010)
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) (2010)
Holger Höfling, Robert Tibshirani
Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods. J. Mach. Learn. Res. 10 (2009)
Trevor Hastie, Jerome H. Friedman, Robert Tibshirani
Regularization paths and coordinate descent. KDD (2008)
Monica Nicolau, Robert Tibshirani, Anne-Lise Børresen-Dale, Stefanie S. Jeffrey
Disease-specific genomic analysis: identifying the signature of pathologic biology. Bioinform. 23 (8) (2007)
Robert Tibshirani, Trevor Hastie
Margin Trees for High-dimensional Classification. J. Mach. Learn. Res. 8 (2007)
Robert Tibshirani
A simple method for assessing sample sizes in microarray experiments. BMC Bioinform. 7 (2006)
Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu
The Entire Regularization Path for the Support Vector Machine. J. Mach. Learn. Res. 5 (2004)
Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu
The Entire Regularization Path for the Support Vector Machine. NIPS (2004)
Kamesh Munagala, Robert Tibshirani, Patrick O. Brown
Cancer characterization and feature set extraction by discriminative margin clustering. BMC Bioinform. 5 (2004)
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) (2004)
Pei Wang, Young Kim, Jonathan R. Pollack, Robert Tibshirani
Boosted PRIM with Application to Searching for Oncogenic Pathway of Lung Cancer. CSB (2004)
Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibshirani
1-norm Support Vector Machines. NIPS (2003)
Eric Bair, Robert Tibshirani
Machine learning methods applied to DNA microarray data can improve the diagnosis of cancer. SIGKDD Explor. 5 (2) (2003)
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) (2003)
Trevor Hastie, Robert Tibshirani, Balasubramanian Narasimhan, Gilbert Chu
Supervised Learning from Microarray Data. COMPSTAT (2002)
Trevor Hastie, Robert Tibshirani
Independent Components Analysis through Product Density Estimation. NIPS (2002)
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) (2001)
Robert Tibshirani, Geoffrey E. Hinton
Coaching variables for regression and classification. Stat. Comput. 8 (1) (1998)
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) (1996)
Robert Tibshirani
A Comparison of Some Error Estimates for Neural Network Models. Neural Comput. 8 (1) (1996)
Trevor Hastie, Robert Tibshirani
Discriminant Adaptive Nearest Neighbor Classification and Regression. NIPS (1995)
Trevor Hastie, Robert Tibshirani
Discriminant Adaptive Nearest Neighbor Classification. KDD (1995)