Trevor Hastie - RankMe

85 papers A* 8A 1B 1Journal 55Unranked 18

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	ExpFamilyPCA.jl: A Julia Package for Exponential Family Principal Component Analysis. J. Open Source Softw. Logan Mondal Bhamidipaty, Mykel J. Kochenderfer, Trevor Hastie
2025	J	`jnl`	Fitting Multilevel Factor Models. SIAM J. Matrix Anal. Appl. Tetiana Parshakova, Trevor Hastie, Stephen P. Boyd
2025	J	`jnl`	Non-smooth optimization meets automated material model discovery. CoRR Moritz Flaschel, Trevor Hastie, Ellen Kuhl
2025	J	`jnl`	Note on the Equivalence of Orthogonalizing EM and Proximal Gradient Descent. Technometrics James Yang, Trevor Hastie
2024	J	`jnl`	A Fast and Scalable Pathwise-Solver for Group Lasso and Elastic Net Penalized Regression via Block-Coordinate Descent. CoRR James Yang, Trevor Hastie
2024	J	`jnl`	A randomized clinical trial testing digital mindset intervention for knee osteoarthritis pain and activity improvement. npj Digit. Medicine Melissa A. Boswell, Kris M. Evans, Disha Ghandwani, Trevor Hastie, Sean R. Zion, Paula Moya, Nicholas J. Giori, Jennifer L. Hicks, Alia Crum, Scott L. Delp
2024	J	`jnl`	Fitting Multilevel Factor Models. CoRR Tetiana Parshakova, Trevor Hastie, Stephen Boyd
2024	J	`jnl`	MMIL: A novel algorithm for disease associated cell type discovery. CoRR Erin Craig, Timothy Keyes, Jolanda Sarno, Maxim Zaslavsky, Garry Nolan, Kara Davis, Trevor Hastie, Robert Tibshirani
2024	J	`jnl`	Modeling Longitudinal Data Using Matrix Completion. J. Comput. Graph. Stat. Lukasz Kidzinski, Trevor Hastie
2024	J	`jnl`	Scalable recommender system based on factor analysis. CoRR Disha Ghandwani, Trevor Hastie
2024	J	`jnl`	Using Pre-training and Interaction Modeling for ancestry-specific disease prediction in UK Biobank. CoRR Thomas Le Menestrel, Erin Craig, Robert Tibshirani, Trevor Hastie, Manuel A. Rivas
2023	J	`jnl`	A Statistical View of Column Subset Selection. CoRR Anav Sood, Trevor Hastie
2023	J	`jnl`	Elastic Net Regularization Paths for All Generalized Linear Models. J. Stat. Softw. J. Kenneth Tay, Balasubramanian Narasimhan, Trevor Hastie
2023	J	`jnl`	Factor Fitting, Rank Allocation, and Partitioning in Multilevel Low Rank Matrices. CoRR Tetiana Parshakova, Trevor Hastie, Eric Darve, Stephen Boyd
2022	J	`jnl`	LinCDE: Conditional Density Estimation via Lindsey's Method. J. Mach. Learn. Res. Zijun Gao, Trevor Hastie
2022	J	`jnl`	RbX: Region-based explanations of prediction models. CoRR Ismael Lemhadri, Harrison H. Li, Trevor Hastie
2022	J	`jnl`	Shark detection and classification with machine learning. Ecol. Informatics Jeremy Jenrette, Zac Yung-Chun Liu, P. Chimote, Trevor Hastie, E. Fox, Francesco Ferretti
2021	J	`jnl`	Fast numerical optimization for genome sequencing data in population biobanks. Bioinform. Ruilin Li, Christopher Chang, Yosuke Tanigawa, Balasubramanian Narasimhan, Trevor Hastie, Robert Tibshirani, Manuel A. Rivas
2021	J	`jnl`	Survival analysis on rare events using group-regularized multi-response Cox regression. Bioinform. Ruilin Li, Yosuke Tanigawa, Johanne M. Justesen, Jonathan Taylor, Trevor Hastie, Robert Tibshirani, Manuel A. Rivas
2021	J	`jnl`	Weighted Low Rank Matrix Approximation and Acceleration. CoRR Elena Tuzhilina, Trevor Hastie
2020	J	`jnl`	Feature-weighted elastic net: using "features of features" for better prediction. CoRR J. Kenneth Tay, Nima Aghaeepour, Trevor Hastie, Robert Tibshirani
2020	J	`jnl`	Generalized Matrix Factorization. CoRR Lukasz Kidzinski, Francis K. C. Hui, David I. Warton, Trevor Hastie
2020	J	`jnl`	Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions. Nat. Mach. Intell. 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
2020	J	`jnl`	Ridge Regularization: An Essential Concept in Data Science. Technometrics Trevor Hastie
2020	J	`jnl`	Ridge Regularizaton: an Essential Concept in Data Science. CoRR Trevor Hastie
2020	J	`jnl`	Simultaneous Relevance and Diversity: A New Recommendation Inference Approach. CoRR Yifang Liu, Zhentao Xu, Qiyuan An, Yang Yi, Yanzhi Wang, Trevor Hastie
2019	J	`jnl`	Surprises in High-Dimensional Ridgeless Least Squares Interpolation. CoRR Trevor Hastie, Andrea Montanari, Saharon Rosset, Ryan J. Tibshirani
2018	J	`jnl`	Longitudinal data analysis using matrix completion. CoRR Lukasz Kidzinski, Trevor Hastie
2017	J	`jnl`	Saturating Splines and Feature Selection. J. Mach. Learn. Res. Nicholas Boyd, Trevor Hastie, Stephen P. Boyd, Benjamin Recht, Michael I. Jordan
2017	J	`jnl`	Synergistic drug combinations from electronic health records and gene expression. J. Am. Medical Informatics Assoc. Yen S. Low, Aaron C. Daugherty, Elizabeth A. Schroeder, William Chen, Tina Seto, Susan C. Weber, Michael Lim, Trevor Hastie, Maya Mathur, Manisha Desai, Carl Farrington, Andrew A. Radin, Marina Sirota, Pragati Kenkare, Caroline A. Thompson, Peter P. Yu, Scarlett L. Gomez, George W. Sledge, Allison W. Kurian, Nigam H. Shah
2015	J	`jnl`	Matrix completion and low-rank SVD via fast alternating least squares. J. Mach. Learn. Res. Trevor Hastie, Rahul Mazumder, Jason D. Lee, Reza Zadeh
2015	J	`jnl`	Telugu OCR Framework using Deep Learning. CoRR Rakesh Achanta, Trevor Hastie
2015	J	`jnl`	The mobilize center: an NIH big data to knowledge center to advance human movement research and improve mobility. J. Am. Medical Informatics Assoc. Joy P. Ku, Jennifer L. Hicks, Trevor Hastie, Jure Leskovec, Christopher Ré, Scott L. Delp
2014	J	`jnl`	Confidence intervals for random forests: the jackknife and the infinitesimal jackknife. J. Mach. Learn. Res. Stefan Wager, Trevor Hastie, Bradley Efron
2013	A	`conf`	Structure Learning of Mixed Graphical Models. AISTATS Jason D. Lee, Trevor Hastie
2012	J	`jnl`	Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso. J. Mach. Learn. Res. Rahul Mazumder, Trevor Hastie
2012	J	`jnl`	Learning Mixed Graphical Models CoRR Jason D. Lee, Trevor Hastie
2011	J	`jnl`	Sparse Discriminant Analysis. Technometrics Line H. Clemmensen, Trevor Hastie, Daniela M. Witten, Bjarne K. Ersbøll
2011	J	`jnl`	The Graphical Lasso: New Insights and Alternatives CoRR Rahul Mazumder, Trevor Hastie
2010	J	`jnl`	Dynamic visualization of statistical learning in the context of high-dimensional textual data. J. Web Semant. Michael Greenacre, Trevor Hastie
2010	J	`jnl`	Network-Based Elucidation of Human Disease Similarities Reveals Common Functional Modules Enriched for Pluripotent Drug Targets. PLoS Comput. Biol. Silpa Suthram, Joel Dudley, Annie P. Chiang, Rong Chen, Trevor Hastie, Atul J. Butte
2010	J	`jnl`	Spectral Regularization Algorithms for Learning Large Incomplete Matrices. J. Mach. Learn. Res. Rahul Mazumder, Trevor Hastie, Robert Tibshirani
2009	J	`jnl`	Genome-wide association analysis by lasso penalized logistic regression. Bioinform. Tong Tong Wu, Yi Fang Chen, Trevor Hastie, Eric M. Sobel, Kenneth Lange
2009	—	`book`	The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition. Trevor Hastie, Robert Tibshirani, Jerome H. Friedman
2008	—	`conf`	One sketch for all: Theory and Application of Conditional Random Sampling. NIPS Ping Li, Kenneth Ward Church, Trevor Hastie
2008	A*	`conf`	Regularization paths and coordinate descent. KDD Trevor Hastie, Jerome H. Friedman, Robert Tibshirani
2007	—	`conf`	A Unified Near-Optimal Estimator For Dimension Reduction in l NIPS Ping Li, Trevor Hastie
2007	J	`jnl`	Margin Trees for High-dimensional Classification. J. Mach. Learn. Res. Robert Tibshirani, Trevor Hastie
2007	A*	`conf`	Nonlinear Estimators and Tail Bounds for Dimension Reduction in COLT Ping Li, Trevor Hastie, Kenneth Ward Church
2007	J	`jnl`	Nonlinear Estimators and Tail Bounds for Dimension Reduction in J. Mach. Learn. Res. Ping Li, Trevor Hastie, Kenneth Ward Church
2006	—	`conf`	Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data. NIPS Ping Li, Kenneth Ward Church, Trevor Hastie
2006	A*	`conf`	Improving Random Projections Using Marginal Information. COLT Ping Li, Trevor Hastie, Kenneth Ward Church
2006	J	`jnl`	Nonlinear Estimators and Tail Bounds for Dimension Reduction in $l_1$ Using Cauchy Random Projections CoRR Ping Li, Trevor Hastie, Kenneth Ward Church
2006	A*	`conf`	Very sparse random projections. KDD Ping Li, Trevor Hastie, Kenneth Ward Church
2005	J	`jnl`	Representing cyclic human motion using functional analysis. Image Vis. Comput. Dirk Ormoneit, Michael J. Black, Trevor Hastie, Hedvig Kjellström
2004	—	`conf`	A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning. NIPS Saharon Rosset, Ji Zhu, Hui Zou, Trevor Hastie
2004	J	`jnl`	Boosting as a Regularized Path to a Maximum Margin Classifier. J. Mach. Learn. Res. Saharon Rosset, Ji Zhu, Trevor Hastie
2004	J	`jnl`	Sample classification from protein mass spectrometry, by 'peak probability contrasts'. Bioinform. Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan, Scott G. Soltys, Gongyi Shi, Albert C. Koong, Quynh-Thu Le
2004	—	`conf`	The Entire Regularization Path for the Support Vector Machine. NIPS Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu
2004	J	`jnl`	The Entire Regularization Path for the Support Vector Machine. J. Mach. Learn. Res. Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu
2004	A*	`conf`	The Sentimental Factor: Improving Review Classification Via Human-Provided Information. ACL Philip Beineke, Trevor Hastie, Shivakumar Vaithyanathan
2003	—	`conf`	1-norm Support Vector Machines. NIPS Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibshirani
2003	—	`conf`	Boosting and support vector machines as optimal separators. DRR Saharon Rosset, Ji Zhu, Trevor Hastie
2003	—	`conf`	Margin Maximizing Loss Functions. NIPS Saharon Rosset, Ji Zhu, Trevor Hastie
2003	J	`jnl`	Note on "Comparison of Model Selection for Regression" by Vladimir Cherkassky and Yunqian Ma. Neural Comput. Trevor Hastie, Robert Tibshirani, Jerome H. Friedman
2002	—	`conf`	Independent Components Analysis through Product Density Estimation. NIPS Trevor Hastie, Robert Tibshirani
2002	—	`conf`	Supervised Learning from Microarray Data. COMPSTAT Trevor Hastie, Robert Tibshirani, Balasubramanian Narasimhan, Gilbert Chu
2002	—	`conf`	Support Vector Machines, Kernel Logistic Regression and Boosting. Multiple Classifier Systems Ji Zhu, Trevor Hastie
2001	—	`conf`	Kernel Logistic Regression and the Import Vector Machine. NIPS Ji Zhu, Trevor Hastie
2001	J	`jnl`	Missing value estimation methods for DNA microarrays. Bioinform. Olga G. Troyanskaya, Michael N. Cantor, Gavin Sherlock, Patrick O. Brown, Trevor Hastie, Robert Tibshirani, David Botstein, Russ B. Altman
2001	—	`book`	The Elements of Statistical Learning: Data Mining, Inference, and Prediction Trevor Hastie, Jerome H. Friedman, Robert Tibshirani
2000	—	`conf`	Learning and Tracking Cyclic Human Motion. NIPS Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black, Trevor Hastie
1999	—	`conf`	Optimal Kernel Shapes for Local Linear Regression. NIPS Dirk Ormoneit, Trevor Hastie
1998	J	`jnl`	Regression Analysis of Multiple Protein Structures. J. Comput. Biol. Thomas D. Wu, Scott C. Schmidler, Trevor Hastie, Douglas L. Brutlag
1998	B	`conf`	Regression analysis of multiple protein structures. RECOMB Thomas D. Wu, Trevor Hastie, Scott C. Schmidler, Douglas L. Brutlag
1997	—	`conf`	Classification by Pairwise Coupling. NIPS Trevor Hastie, Robert Tibshirani
1997	A*	`conf`	Discriminative vs Informative Learning. KDD Y. Dan Rubinstein, Trevor Hastie
1997	—	`conf`	The Error Coding and Substitution PaCTs. NIPS Gareth James, Trevor Hastie
1996	J	`jnl`	Discriminant Adaptive Nearest Neighbor Classification. IEEE Trans. Pattern Anal. Mach. Intell. Trevor Hastie, Robert Tibshirani
1995	—	`conf`	Discriminant Adaptive Nearest Neighbor Classification and Regression. NIPS Trevor Hastie, Robert Tibshirani
1995	A*	`conf`	Discriminant Adaptive Nearest Neighbor Classification. KDD Trevor Hastie, Robert Tibshirani
1994	—	`conf`	Learning Prototype Models for Tangent Distance. NIPS Trevor Hastie, Patrice Y. Simard
1994	J	`jnl`	Statistical Methods for On-Line Signature Verification. Int. J. Pattern Recognit. Artif. Intell. Winston L. Nelson, William Turin, Trevor Hastie
1991	J	`jnl`	3-D curve matching using splines. J. Field Robotics Eyal Kishon, Trevor Hastie, Haim J. Wolfson
1990	A*	`conf`	3-D Curve Matching Using Splines. ECCV Eyal Kishon, Trevor Hastie, Haim J. Wolfson