Towards AutoML in the presence of Drift: first results

Towards AutoML in the presence of Drift: first results

24 July 2019

Jorge G. Madrid

Hugo Jair Escalante

Lisheng Sun-Hosoya

Isabelle M Guyon

Michele Sebag

Papers citing "Towards AutoML in the presence of Drift: first results"

8 / 8 papers shown

Title
Adaptation Strategies for Automated Machine Learning on Evolving Data B. Celik Joaquin Vanschoren 50 56 0 09 Jun 2020
Lifelong Learning for Sentiment Classification Zhiyuan Chen Nianzu Ma Bing-Quan Liu CLL 58 157 0 09 Jan 2018
Reservoir of Diverse Adaptive Learners and Stacking Fast Hoeffding Drift Detection Methods for Evolving Data Streams Ali Pesaranghader H. Viktor E. Paquet 37 65 0 07 Sep 2017
Large-Scale Evolution of Image Classifiers Esteban Real Sherry Moore Andrew Selle Saurabh Saxena Y. Suematsu Jie Tan Quoc V. Le Alexey Kurakin 125 1,640 0 03 Mar 2017
Designing Neural Network Architectures using Reinforcement Learning Bowen Baker O. Gupta Nikhil Naik Ramesh Raskar 110 1,471 0 07 Nov 2016
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 459 5,372 0 05 Nov 2016
OpenML: networked science in machine learning Joaquin Vanschoren Jan N. van Rijn B. Bischl Luís Torgo FedML AI4CE 163 1,324 0 29 Jul 2014
Freeze-Thaw Bayesian Optimization Kevin Swersky Jasper Snoek Ryan P. Adams 79 269 0 16 Jun 2014