Hastie, Trevor

The Elements of Statistical Learning

Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics

Statistical Methods and ApplicationsStatistical Methods and Inference

Cited by 25,970

The Elements of Statistical Learning

Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics

Statistical Methods and InferenceStatistical Methods and Applications

Cited by 24,162

Regularization and Variable Selection Via the Elastic Net

Zou, H., & Hastie, T. (2005) · Journal of the Royal Statistical Society Series B: Statistical Methodology

Statistical Methods and InferenceAdvanced Statistical Methods and Models

Cited by 20,957

Regularization Paths for Generalized Linear Models via Coordinate Descent

Friedman, J., Hastie, T., & Tibshirani, R. (2010) · Journal of Statistical Software

Statistical Methods and InferenceStochastic Gradient Optimization Techniques

Cited by 19,927

An Introduction to Statistical Learning

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013) · Springer Texts in Statistics

Statistical Methods and ApplicationsStatistical Methods and Inference

Cited by 12,106

Least angle regression

Efron, B., Hastie, T., Johnstone, I., & Tibshirani, R. (2004) · The Annals of Statistics

Statistical Methods and InferenceAdvanced Statistical Methods and Models

Cited by 9,357

Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors)

Friedman, J., Hastie, T., & Tibshirani, R. (2000) · The Annals of Statistics

Imbalanced Data Classification TechniquesStatistical Methods and Inference

Cited by 6,884

A statistical explanation of MaxEnt for ecologists

Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E., & Yates, C. J. (2011) · Diversity and Distributions

Species Distribution and Climate ChangeEcology and Vegetation Dynamics Studies

Cited by 6,699

A working guide to boosted regression trees

Elith, J., Leathwick, J. R., & Hastie, T. (2008) · Journal of Animal Ecology

Species Distribution and Climate ChangeStatistical Methods and Applications

Cited by 6,484

Sparse inverse covariance estimation with the graphical lasso

Friedman, J., Hastie, T., & Tibshirani, R. (2008) · Biostatistics

Statistical Methods and InferenceSparse and Compressive Sensing Techniques

Cited by 6,355

Estimating the Number of Clusters in a Data Set Via the Gap Statistic

Tibshirani, R., Walther, G., & Hastie, T. (2001) · Journal of the Royal Statistical Society Series B: Statistical Methodology

Advanced Clustering Algorithms ResearchBayesian Methods and Mixture Models

Cited by 6,205

Missing Value Estimation Methods for DNA Microarrays

Troyanskaya, O., Cantor, M., Sherlock, G., Brown, P., Hastie, T., Tibshirani, R., Botstein, D., & Altman, R. B. (2001) · Bioinformatics

Gene expression and cancer classificationGenomics and Phylogenetic Studies

Cited by 4,230

Sparse Principal Component Analysis

Zou, H., Hastie, T., & Tibshirani, R. (2006) · Journal of Computational and Graphical Statistics

Statistical Methods and InferenceStatistical Methods and Applications

Cited by 3,152

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

Ioannidis, N. M., Rothstein, J. H., Pejaver, V., Middha, S., McDonnell, S. K., Baheti, S., Musolf, A., Li, Q., Holzinger, E., Karyadi, D., et al. (2016) · The American Journal of Human Genetics

Genomics and Rare DiseasesGenetic Associations and Epidemiology

Cited by 2,908

Generalized linear and generalized additive models in studies of species distributions: setting the scene

Guisan, A., Edwards, T. C., & Hastie, T. (2002) · Ecological Modelling

Species Distribution and Climate ChangeStatistical Methods and Applications

Cited by 2,356

A Sparse-Group Lasso

Simon, N., Friedman, J., Hastie, T., & Tibshirani, R. (2013) · Journal of Computational and Graphical Statistics

Statistical Methods and InferenceSparse and Compressive Sensing Techniques

Cited by 1,380

Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival

Chang, H. Y., Nuyten, D. S. A., Sneddon, J. B., Hastie, T., Tibshirani, R., Sørlie, T., Dai, H., He, Y. D., van't Veer, L. J., Bartelink, H., et al. (2005) · Proceedings of the National Academy of Sciences

Breast Cancer Treatment StudiesGene expression and cancer classification

Cited by 981

Genome-wide association analysis by lasso penalized logistic regression

Wu, T. T., Chen, Y. F., Hastie, T., Sobel, E., & Lange, K. (2009) · Bioinformatics

Genetic Associations and EpidemiologyStatistical Methods and Inference

Cited by 785

Genetics of 35 blood and urine biomarkers in the UK Biobank

Sinnott-Armstrong, N., Tanigawa, Y., Amar, D., Mars, N., Benner, C., Aguirre, M., Venkataraman, G. R., Wainberg, M., Ollila, H. M., Kiiskinen, T., et al. (2021) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 744

Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort

Shcherbina, A., Mattsson, C., Waggott, D., Salisbury, H., Christle, J., Hastie, T., Wheeler, M., & Ashley, E. (2017) · Journal of Personalized Medicine

Non-Invasive Vital Sign MonitoringContext-Aware Activity Recognition Systems

Cited by 625

An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging

Sayed, N., Huang, Y., Nguyen, K., Krejciova-Rajaniemi, Z., Grawe, A. P., Gao, T., Tibshirani, R., Hastie, T., Alpert, A., Cui, L., et al. (2021) · Nature Aging

Genetics, Aging, and Longevity in Model OrganismsTelomeres, Telomerase, and Senescence

Cited by 572

'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns

Hastie, T., Tibshirani, R., Eisen, M. B., Alizadeh, A., Levy, R., Staudt, L., Chan, W. C., Botstein, D., & Brown, P. (2000) · Genome Biology

Gene expression and cancer classificationBioinformatics and Genomic Networks

Cited by 547

Transparency and reproducibility in artificial intelligence

Haibe-Kains, B., Adam, G. A., Hosny, A., Khodakarami, F., Massive Analysis Quality Control (MAQC) Society Board of Directors, Shraddha, T., Kusko, R., Sansone, S.-A., Tong, W., Wolfinger, R. D., et al. (2020) · Nature

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 540

Wearable sensors enable personalized predictions of clinical laboratory measurements

Dunn, J., Kidzinski, L., Runge, R., Witt, D., Hicks, J. L., Schüssler-Fiorenza Rose, S. M., Li, X., Bahmani, A., Delp, S. L., Hastie, T., et al. (2021) · Nature Medicine

Non-Invasive Vital Sign MonitoringArtificial Intelligence in Healthcare

Cited by 244