An Introduction to the Bootstrap - Bradley Efron; Robert Tibshirani (Springer, 1993)

Discriminant Adaptive Nearest Neighbor Classification and Regression. - Trevor Hastie; Robert Tibshirani (NIPS, 1995)

A Comparison of Some Error Estimates for Neural Network Models. - Robert Tibshirani (Neural Comput., 1996)

Discriminant Adaptive Nearest Neighbor Classification. - Trevor Hastie; Robert Tibshirani (IEEE Trans. Pattern Anal. Mach. Intell., 1996)

Classification by Pairwise Coupling. - Trevor Hastie; Robert Tibshirani (NIPS, 1997)

Coaching variables for regression and classification. - Robert Tibshirani; Geoffrey E. Hinton (Stat. Comput., 1998)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction - Trevor Hastie; Jerome H. Friedman; Robert Tibshirani (Springer, 2001)

Missing value estimation methods for DNA microarrays. - Olga G. Troyanskaya; Michael N. Cantor; Gavin Sherlock; Patrick O. Brown; Trevor Hastie; Robert Tibshirani; David Botstein; Russ B. Altman (Bioinform., 2001)

Supervised Learning from Microarray Data. - Trevor Hastie; Robert Tibshirani; Balasubramanian Narasimhan; Gilbert Chu (COMPSTAT, 2002)

Independent Components Analysis through Product Density Estimation. - Trevor Hastie; Robert Tibshirani (NIPS, 2002)

1-norm Support Vector Machines. - Ji Zhu 001; Saharon Rosset; Trevor Hastie; Robert Tibshirani (NIPS, 2003)

Note on "Comparison of Model Selection for Regression" by Vladimir Cherkassky and Yunqian Ma. - Trevor Hastie; Robert Tibshirani; Jerome H. Friedman (Neural Comput., 2003)

Machine learning methods applied to DNA microarray data can improve the diagnosis of cancer. - Eric Bair; Robert Tibshirani (SIGKDD Explor., 2003)

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

Sample classification from protein mass spectrometry, by 'peak probability contrasts'. - Robert Tibshirani; Trevor Hastie; Balasubramanian Narasimhan; Scott G. Soltys; Gongyi Shi; Albert C. Koong; Quynh-Thu Le (Bioinform., 2004)

Cancer characterization and feature set extraction by discriminative margin clustering. - Kamesh Munagala; Robert Tibshirani; Patrick O. Brown (BMC Bioinform., 2004)

The Entire Regularization Path for the Support Vector Machine. - Trevor Hastie; Saharon Rosset; Robert Tibshirani; Ji Zhu 001 (J. Mach. Learn. Res., 2004)

43. Who Is the Fastest Man in the World? - Robert Tibshirani (Anthology of Statistics in Sports, 2005)

A simple method for assessing sample sizes in microarray experiments. - Robert Tibshirani (BMC Bioinform., 2006)

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

Margin Trees for High-dimensional Classification. - Robert Tibshirani; Trevor Hastie (J. Mach. Learn. Res., 2007)

Regularization paths and coordinate descent. - Trevor Hastie; Jerome H. Friedman; Robert Tibshirani (KDD, 2008)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition. - Trevor Hastie; Robert Tibshirani; Jerome H. Friedman (Springer, 2009)

Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods. - Holger Höfling; Robert Tibshirani (J. Mach. Learn. Res., 2009)

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

Spectral Regularization Algorithms for Learning Large Incomplete Matrices. - Rahul Mazumder; Trevor Hastie; Robert Tibshirani (J. Mach. Learn. Res., 2010)

Supervised multidimensional scaling for visualization, classification, and bipartite ranking. - Daniela M. Witten; Robert Tibshirani (Comput. Stat. Data Anal., 2011)

Nearly-Isotonic Regression. - Ryan J. Tibshirani; Holger Höfling; Robert Tibshirani (Technometrics, 2011)

A Component Lasso. - Nadine Hussami; Robert Tibshirani (CoRR, 2013)

Scientific research in the age of omics: the good, the bad, and the sloppy. - Daniela M. Witten; Robert Tibshirani (J. Am. Medical Informatics Assoc., 2013)

Sensitivity analysis for inference with partially identifiable covariance matrices. - Max Grazier G'Sell; Shai S. Shen-Orr; Robert Tibshirani (Comput. Stat., 2014)

Noninvasive Cancer Classification Using Diverse Genomic Features in Circulating Tumor DNA. - Mohammad Shahrokh Esfahani; Aaron M. Newman; Florian Scherer; Robert Tibshirani; Maximilian Diehn; Ash A. Alizadeh (BCB, 2016)

Data Shared Lasso: A novel tool to discover uplift. - Samuel M. Gross; Robert Tibshirani (Comput. Stat. Data Anal., 2016)

An Ordered Lasso and Sparse Time-Lagged Regression. - Robert Tibshirani; Xiaotong Suo (Technometrics, 2016)

Chemical Space Mimicry for Drug Discovery. - 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; et al. (J. Chem. Inf. Model., 2017)

Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy. - 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; et al. (Bioinform., 2019)

Spectral Overlap and a Comparison of Parameter-Free, Dimensionality Reduction Quality Metrics. - Jonathan Johannemann; Robert Tibshirani (CoRR, 2019)

A neural network with feature sparsity. - Ismael Lemhadri; Feng Ruan; Robert Tibshirani (CoRR, 2019)

Feature-weighted elastic net: using "features of features" for better prediction. - J. Kenneth Tay; Nima Aghaeepour; Trevor Hastie; Robert Tibshirani (CoRR, 2020)

Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions. - Anthony Culos; Amy Tsai; Natalie Stanley; Martin Becker 003; Mohammad Sajjad Ghaemi; David Mcilwain; Ramin Fallahzadeh; Athena Tanada; Huda Nassar; Camilo Espinosa; Maria Xenochristou; Edward Ganio; et al. (Nat. Mach. Intell., 2020)

LassoNet: Neural Networks with Feature Sparsity. - Ismael Lemhadri; Feng Ruan; Robert Tibshirani (AISTATS, 2021)

Survival analysis on rare events using group-regularized multi-response Cox regression. - Ruilin Li; Yosuke Tanigawa; Johanne M. Justesen; Jonathan Taylor; Trevor Hastie; Robert Tibshirani; Manuel A. Rivas (Bioinform., 2021)

MassExplorer: a computational tool for analyzing desorption electrospray ionization mass spectrometry data. - Vishnu Shankar; Robert Tibshirani; Richard N. Zare (Bioinform., 2021)

LassoNet: A Neural Network with Feature Sparsity. - Ismael Lemhadri; Feng Ruan; Louis Abraham; Robert Tibshirani (J. Mach. Learn. Res., 2021)

De novo mutational signature discovery in tumor genomes using SparseSignatures. - Avantika Lal; Keli Liu; Robert Tibshirani; Arend Sidow; Daniele Ramazzotti (PLoS Comput. Biol., 2021)

Fast numerical optimization for genome sequencing data in population biobanks. - Ruilin Li; Christopher Chang; Yosuke Tanigawa; Balasubramanian Narasimhan; Trevor Hastie; Robert Tibshirani; Manuel A. Rivas (Bioinform., 2021)

FastCPH: Efficient Survival Analysis for Neural Networks. - Xuelin Yang; Louis Abraham; Sejin Kim; Petr Smirnov; Feng Ruan; Benjamin Haibe-Kains; Robert Tibshirani (CoRR, 2022)

Semi-supervised Cooperative Learning for Multiomics Data Fusion. - Daisy Yi Ding; Xiaotao Shen; Michael Snyder 001; Robert Tibshirani (ML4MHD, 2023)

Using Pre-training and Interaction Modeling for ancestry-specific disease prediction in UK Biobank. - Thomas Le Menestrel; Erin Craig; Robert Tibshirani; Trevor Hastie; Manuel A. Rivas (CoRR, 2024)

MMIL: A novel algorithm for disease associated cell type discovery. - Erin Craig; Timothy Keyes; Jolanda Sarno; Maxim Zaslavsky; Garry Nolan; Kara Davis; Trevor Hastie; Robert Tibshirani (CoRR, 2024)

Semiparametric conformal prediction. - Ji Won Park; Robert Tibshirani; Kyunghyun Cho (CoRR, 2024)

Smooth Multi-Period Forecasting With Application to Prediction of COVID-19 Cases. - Elena Tuzhilina; Trevor J. Hastie; Daniel J. McDonald; J. Kenneth Tay; Robert Tibshirani (J. Comput. Graph. Stat., 2024)

Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study. - 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; et al. (npj Digit. Medicine, 2024)

BIOMEDICA: An Open Biomedical Image-Caption Archive, Dataset, and Vision-Language Models Derived from Scientific Literature. - Alejandro Lozano; Min Woo Sun; James Burgess; Liangyu Chen 005; Jeffrey J. Nirschl; Jeffrey Gu; Ivan Lopez; Josiah Aklilu; Anita Rau; Austin Wolfgang Katzer; Yuhui Zhang; Collin Chiu; et al. (CVPR, 2025)

LLM-Lasso: A Robust Framework for Domain-Informed Feature Selection and Regularization. - Erica Zhang; Ryunosuke Goto; Naomi Sagan; Jurik Mutter; Nick Phillips; Ash A. Alizadeh; Kangwook Lee 001; Jose Blanchet; Mert Pilanci; Robert Tibshirani (CoRR, 2025)

A Large-Scale Vision-Language Dataset Derived from Open Scientific Literature to Advance Biomedical Generalist AI. - Alejandro Lozano; Min Woo Sun; James Burgess; Jeffrey J. Nirschl; Christopher Polzak; Yuhui Zhang; Liangyu Chen 005; Jeffrey Gu; Ivan Lopez; Josiah Aklilu; Anita Rau; Austin Wolfgang Katzer; et al. (CoRR, 2025)

Statistical Learning for Heterogeneous Treatment Effects: Pretraining, Prognosis, and Prediction. - Maximilian Schüßler; Erik Sverdrup; Robert Tibshirani (CoRR, 2025)