KTBoost: Combined Kernel and Tree Boosting

11 February 2019

Papers citing "KTBoost: Combined Kernel and Tree Boosting"

19 / 19 papers shown

Title
SEEK: Self-adaptive Explainable Kernel For Nonstationary Gaussian Processes Nima Negarandeh Carlos Mora Ramin Bostanabad 88 0 0 18 Mar 2025
On the minimax optimality and superiority of deep neural network learning over sparse parameter spaces Satoshi Hayakawa Taiji Suzuki 38 48 0 22 May 2019
Gradient and Newton Boosting for Classification and Regression Fabio Sigrist 50 62 0 09 Aug 2018
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate M. Belkin Daniel J. Hsu P. Mitra AI4CE 146 259 0 13 Jun 2018
Functional Gradient Boosting based on Residual Network Perception Atsushi Nitanda Taiji Suzuki 63 27 0 25 Feb 2018
Deep Neural Networks Learn Non-Smooth Functions Effectively Masaaki Imaizumi Kenji Fukumizu 148 124 0 13 Feb 2018
To understand deep learning we need to understand kernel learning M. Belkin Siyuan Ma Soumik Mandal 70 420 0 05 Feb 2018
TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting Natalia Ponomareva Soroush Radpour Gilbert Hendry Salem Haykal Thomas Colthurst Petr Mitrichev Alexander Grushetsky AI4CE 54 23 0 31 Oct 2017
Early stopping for kernel boosting algorithms: A general analysis with localized complexities Yuting Wei Fanny Yang Martin J. Wainwright 66 77 0 05 Jul 2017
Learning Deep ResNet Blocks Sequentially using Boosting Theory Furong Huang Jordan T. Ash John Langford Robert Schapire 86 111 0 15 Jun 2017
Diving into the shallows: a computational perspective on large-scale shallow learning Siyuan Ma M. Belkin 64 78 0 30 Mar 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 348 4,635 0 10 Nov 2016
Estimation and Prediction using generalized Wendland Covariance Functions under fixed domain asymptotics M. Bevilacqua Tarik Faouzi Reinhard Furrer Emilio Porcu 91 75 0 23 Jul 2016
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 814 39,062 0 09 Mar 2016
Explaining the Success of AdaBoost and Random Forests as Interpolating Classifiers A. Wyner Matthew A. Olson J. Bleich David Mease 95 269 0 28 Apr 2015
Scalable Kernel Methods via Doubly Stochastic Gradients Bo Dai Bo Xie Niao He Yingyu Liang Anant Raj Maria-Florina Balcan Le Song 146 230 0 21 Jul 2014
Early stopping and non-parametric regression: An optimal data-dependent stopping rule Garvesh Raskutti Martin J. Wainwright Bin Yu 119 299 0 15 Jun 2013
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates Yuchen Zhang John C. Duchi Martin J. Wainwright 325 379 0 22 May 2013
Optimal learning rates for Kernel Conjugate Gradient regression Gilles Blanchard Nicole Krämer 94 71 0 29 Sep 2010