Search Results - "Hastie, Trevor"

Learning Interactions via Hierarchical Group-Lasso Regularization by Lim, Michael, Hastie, Trevor

“…We introduce a method for learning pairwise interactions in a linear regression or logistic regression model in a manner that satisfies strong hierarchy:…”
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Best Subset, Forward Stepwise or Lasso? Analysis and Recommendations Based on Extensive Comparisons by Hastie, Trevor, Tibshirani, Robert, Tibshirani, Ryan

“…In exciting recent work, Bertsimas, King and Mazumder (Ann. Statist. 44 (2016) 813–852) showed that the classical best subset selection problem in regression…”
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Elastic Net Regularization Paths for All Generalized Linear Models by Tay, J Kenneth, Narasimhan, Balasubramanian, Hastie, Trevor

“…The lasso and elastic net are popular regularized regression models for supervised learning. Friedman, Hastie, and Tibshirani (2010) introduced a…”
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Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent by Simon, Noah, Friedman, Jerome, Hastie, Trevor, Tibshirani, Rob

“…We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of ℓ and ℓ penalties (elastic net). Our algorithm…”
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Regularization Paths for Generalized Linear Models via Coordinate Descent by Friedman, Jerome, Hastie, Trevor, Tibshirani, Rob

“…We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic…”
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Inference from presence-only data; the ongoing controversy by Hastie, Trevor, Fithian, Will

“…Presence-only data abounds in ecology, often accompanied by a background sample. Although many interesting aspects of the species' distribution can be learned…”
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Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities by Halilaj, Eni, Rajagopal, Apoorva, Fiterau, Madalina, Hicks, Jennifer L., Hastie, Trevor J., Delp, Scott L.

“…Traditional laboratory experiments, rehabilitation clinics, and wearable sensors offer biomechanists a wealth of data on healthy and pathological movement. To…”
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Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets by Suthram, Silpa, Dudley, Joel T, Chiang, Annie P, Chen, Rong, Hastie, Trevor J, Butte, Atul J

“…Current work in elucidating relationships between diseases has largely been based on pre-existing knowledge of disease genes. Consequently, these studies are…”
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Learning the Structure of Mixed Graphical Models by Lee, Jason D., Hastie, Trevor J.

“…We consider the problem of learning the structure of a pairwise graphical model over continuous and discrete variables. We present a new pairwise model for…”
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The graphical lasso: New insights and alternatives by Mazumder, Rahul, Hastie, Trevor

“…The graphical lasso [5] is an algorithm for learning the structure in an undirected Gaussian graphical model, using ℓ regularization to control the number of…”
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Significant sparse polygenic risk scores across 813 traits in UK Biobank by Tanigawa, Yosuke, Qian, Junyang, Venkataraman, Guhan, Justesen, Johanne Marie, Li, Ruilin, Tibshirani, Robert, Hastie, Trevor, Rivas, Manuel A

“…We present a systematic assessment of polygenic risk score (PRS) prediction across more than 1,500 traits using genetic and phenotype data in the UK Biobank…”
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Some methods for heterogeneous treatment effect estimation in high dimensions by Powers, Scott, Qian, Junyang, Jung, Kenneth, Schuler, Alejandro, Shah, Nigam H., Hastie, Trevor, Tibshirani, Robert

“…When devising a course of treatment for a patient, doctors often have little quantitative evidence on which to base their decisions, beyond their medical…”
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Regularization and variable selection via the elastic net by Zou, Hui, Hastie, Trevor

“…We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often…”
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L1-regularization path algorithm for generalized linear models by Park, Mee Young, Hastie, Trevor

“…We introduce a path following algorithm forL_{1}$-regularized generalized linear models. TheL_{1}$-regularization procedure is useful especially because it, in…”
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Bias correction in species distribution models: pooling survey and collection data for multiple species by Fithian, William, Elith, Jane, Hastie, Trevor, Keith, David A., O'Hara, Robert B.

“…Summary Presence‐only records may provide data on the distributions of rare species, but commonly suffer from large, unknown biases due to their typically…”
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Decreasing human body temperature in the United States since the industrial revolution by Protsiv, Myroslava, Ley, Catherine, Lankester, Joanna, Hastie, Trevor, Parsonnet, Julie

“…In the US, the normal, oral temperature of adults is, on average, lower than the canonical 37°C established in the 19 century. We postulated that body…”
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A statistical explanation of MaxEnt for ecologists by Elith, Jane, Phillips, Steven J., Hastie, Trevor, Dudík, Miroslav, Chee, Yung En, Yates, Colin J.

“…MaxEnt is a program for modelling species distributions from presence-only species records. This paper is written for ecologists and describes the MaxEnt model…”
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Genetics of 35 blood and urine biomarkers in the UK Biobank by Sinnott-Armstrong, Nasa, Tanigawa, Yosuke, Amar, David, Mars, Nina, Benner, Christian, Aguirre, Matthew, Venkataraman, Guhan Ram, Wainberg, Michael, Ollila, Hanna M., Kiiskinen, Tuomo, Havulinna, Aki S., Pirruccello, James P., Qian, Junyang, Shcherbina, Anna, Rodriguez, Fatima, Assimes, Themistocles L., Agarwala, Vineeta, Tibshirani, Robert, Hastie, Trevor, Ripatti, Samuli, Pritchard, Jonathan K., Daly, Mark J., Rivas, Manuel A.

“…Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the…”
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Genome-wide association analysis by lasso penalized logistic regression by Wu, Tong Tong, Chen, Yi Fang, Hastie, Trevor, Sobel, Eric, Lange, Kenneth

“…Motivation: In ordinary regression, imposition of a lasso penalty makes continuous model selection straightforward. Lasso penalized regression is particularly…”
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Strong rules for discarding predictors in lasso-type problems by Tibshirani, Robert, Bien, Jacob, Friedman, Jerome, Hastie, Trevor, Simon, Noah, Taylor, Jonathan, Tibshirani, Ryan J.

“…We consider rules for discarding predictors in lasso regression and related problems, for computational efficiency. El Ghaoui and his colleagues have proposed…”
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