Selecting Near-Optimal Learners via Incremental Data Allocation

31 December 2015

Papers citing "Selecting Near-Optimal Learners via Incremental Data Allocation"

23 / 23 papers shown

Title
AutoPDL: Automatic Prompt Optimization for LLM Agents Claudio Spiess Mandana Vaziri Louis Mandel Martin Hirzel 62 2 0 06 Apr 2025
Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection Parikshit Ram Alexander G. Gray Horst Samulowitz Gregory Bramble 67 1 0 12 Jan 2023
A Survey on Semantics in Automated Data Science Udayan Khurana Kavitha Srinivas Horst Samulowitz 51 3 0 16 May 2022
Learning Curves for Decision Making in Supervised Machine Learning: A Survey F. Mohr Jan N. van Rijn 112 56 0 28 Jan 2022
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning Yi Zhou Parikshit Ram Theodoros Salonidis Nathalie Baracaldo Horst Samulowitz Heiko Ludwig AI4CE 79 25 0 15 Dec 2021
Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation Ross M. Clarke E. T. Oldewage José Miguel Hernández-Lobato 104 9 0 20 Oct 2021
How Much Automation Does a Data Scientist Want? Dakuo Wang Q. V. Liao Yunfeng Zhang Udayan Khurana Horst Samulowitz Soya Park Michael J. Muller Lisa Amini AI4CE 77 56 0 07 Jan 2021
Efficient Automatic CASH via Rising Bandits Yang Li Jiawei Jiang Jinyang Gao Yingxia Shao Ce Zhang Tengjiao Wang 83 34 0 08 Dec 2020
Solving Constrained CASH Problems with ADMM Parikshit Ram Sijia Liu Deepak Vijaykeerthi Dakuo Wang Djallel Bouneffouf Gregory Bramble Horst Samulowitz Alexander G. Gray 75 3 0 17 Jun 2020
A Survey on Neural Architecture Search Martin Wistuba Ambrish Rawat Tejaswini Pedapati AI4CE 103 259 0 04 May 2019
An ADMM Based Framework for AutoML Pipeline Configuration Sijia Liu Parikshit Ram Deepak Vijaykeerthy Djallel Bouneffouf Gregory Bramble Horst Samulowitz Dakuo Wang A. Conn Alexander G. Gray 119 76 0 01 May 2019
Active Learning for High-Dimensional Binary Features Ali Vahdat Mouloud Belbahri V. Nia 42 5 0 05 Feb 2019
Hyper-parameter Tuning under a Budget Constraint Zhiyun Lu Chao-Kai Chiang Fei Sha 64 17 0 01 Feb 2019
Progressive Sampling-Based Bayesian Optimization for Efficient and Automatic Machine Learning Model Selection Xueqiang Zeng G. Luo 54 75 0 06 Dec 2018
Better Trees: An empirical study on hyperparameter tuning of classification decision tree induction algorithms R. G. Mantovani Tomáš Horváth André L. D. Rossi R. Cerri Sylvio Barbon Junior Joaquin Vanschoren A. Carvalho 69 41 0 05 Dec 2018
Noisy Blackbox Optimization with Multi-Fidelity Queries: A Tree Search Approach Rajat Sen Kirthevasan Kandasamy Sanjay Shakkottai 36 23 0 24 Oct 2018
A System for Massively Parallel Hyperparameter Tuning Liam Li Kevin Jamieson Afshin Rostamizadeh Ekaterina Gonina Moritz Hardt Benjamin Recht Ameet Talwalkar 101 387 0 13 Oct 2018
Population Based Training of Neural Networks Max Jaderberg Valentin Dalibard Simon Osindero Wojciech M. Czarnecki Jeff Donahue ... Tim Green Iain Dunning Karen Simonyan Chrisantha Fernando Koray Kavukcuoglu 132 745 0 27 Nov 2017
An effective algorithm for hyperparameter optimization of neural networks G. I. Diaz Achille Fokoue G. Nannicini Horst Samulowitz 68 158 0 23 May 2017
REMIX: Automated Exploration for Interactive Outlier Detection Yanjie Fu Charu C. Aggarwal Srinivasan Parthasarathy D. Turaga Hui Xiong 32 5 0 17 May 2017
DeepArchitect: Automatically Designing and Training Deep Architectures Renato M. P. Negrinho Geoffrey J. Gordon 109 186 0 28 Apr 2017
Multi-fidelity Bayesian Optimisation with Continuous Approximations Kirthevasan Kandasamy Gautam Dasarathy J. Schneider Barnabás Póczós 76 221 0 18 Mar 2017
Multi-fidelity Gaussian Process Bandit Optimisation Kirthevasan Kandasamy Gautam Dasarathy Junier B. Oliva J. Schneider Barnabás Póczós 101 77 0 20 Mar 2016