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Algorithm Runtime Prediction: Methods & Evaluation

5 November 2012

Holger H. Hoos

Papers citing "Algorithm Runtime Prediction: Methods & Evaluation"

35 / 85 papers shown

Title
Surrogate-assisted performance prediction for data-driven knowledge discovery algorithms: application to evolutionary modeling of clinical pathways Anastasia A. Funkner A. Yakovlev Sergey Kovalchuk 9 6 0 02 Apr 2020
Cost-aware Bayesian Optimization E. Lee Valerio Perrone Cédric Archambeau Matthias Seeger 157 58 0 22 Mar 2020
Towards High Performance, Portability, and Productivity: Lightweight Augmented Neural Networks for Performance Prediction Ajitesh Srivastava Naifeng Zhang Rajgopal Kannan Viktor Prasanna 27 2 0 17 Mar 2020
ENTMOOT: A Framework for Optimization over Ensemble Tree Models Alexander Thebelt Jan Kronqvist Miten Mistry Robert M. Lee Nathan Sudermann-Merx Ruth Misener 89 57 0 10 Mar 2020
From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group) Zied Bouraoui Antoine Cornuéjols Thierry Denoeux Sebastien Destercke Didier Dubois ... Jérôme Mengin H. Prade Steven Schockaert M. Serrurier Christel Vrain 128 14 0 13 Dec 2019
Optimal Decision Trees for the Algorithm Selection Problem: Integer Programming Based Approaches Matheus G. Vilas Boas H. Santos L. Merschmann G. V. Berghe 67 18 0 03 Jul 2019
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration Robert D. Kleinberg Kevin Leyton-Brown Brendan Lucier Devon R. Graham 65 20 0 14 Feb 2019
Which Surrogate Works for Empirical Performance Modelling? A Case Study with Differential Evolution Ke Li Zilin Xiang Kay Chen Tan 65 28 0 30 Jan 2019
Automated Algorithm Selection: Survey and Perspectives P. Kerschke Holger H. Hoos Frank Neumann Heike Trautmann 77 384 0 28 Nov 2018
Meta-Learning: A Survey Joaquin Vanschoren FedML OOD 108 761 0 08 Oct 2018
OBOE: Collaborative Filtering for AutoML Model Selection Chengrun Yang Yuji Akimoto Dae Won Kim Madeleine Udell 61 101 0 09 Aug 2018
Boosting Combinatorial Problem Modeling with Machine Learning M. Lombardi M. Milano AI4CE 78 65 0 15 Jul 2018
Predicting Effective Control Parameters for Differential Evolution using Cluster Analysis of Objective Function Features S. P. Walton M. R. Brown 13 4 0 25 Jun 2018
Predictive Performance Modeling for Distributed Computing using Black-Box Monitoring and Machine Learning Carl Witt M. Bux Wladislaw Gusew Ulf Leser 33 54 0 30 May 2018
The Algorithm Selection Competitions 2015 and 2017 Marius Lindauer Jan N. van Rijn Lars Kotthoff 61 38 0 03 May 2018
Automatic Construction of Parallel Portfolios via Explicit Instance Grouping Shengcai Liu K. Tang Xin Yao 69 29 0 17 Apr 2018
Adaptive online scheduling of tasks with anytime property on heterogeneous resources I. Módos P. Šůcha Roman Václavík J. Smejkal Z. Hanzálek 26 1 0 08 Feb 2018
Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning P. Kerschke Heike Trautmann 102 152 0 24 Nov 2017
Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-Package flacco P. Kerschke 85 102 0 17 Aug 2017
SUNNY-CP and the MiniZinc Challenge R. Amadini M. Gabbrielli J. Mauro 15 5 0 26 Jun 2017
Experience-based Optimization: A Coevolutionary Approach Shengcai Liu K. Tang Xin Yao OffRL 36 4 0 29 Mar 2017
Driving CDCL Search Carmine Dodaro Philip Gasteiger Nicola Leone Benjamin Musitsch Francesco Ricca Konstantin Schekotihin 35 1 0 16 Nov 2016
A case study of algorithm selection for the traveling thief problem Markus Wagner Marius Lindauer Mustafa Misir Samadhi Nallaperuma Frank Hutter 61 66 0 02 Sep 2016
Elastic Solver: Balancing Solution Time and Energy Consumption B. Hurley D. Mehta Barry O'Sullivan 28 3 0 23 May 2016
On the mediation of program allocation in high-demand environments Fabiano de S. Oliveira V. Barbosa 10 0 0 27 Apr 2016
Reinforcement learning based local search for grouping problems: A case study on graph coloring Yangming Zhou Jin-Kao Hao B. Duval 63 69 0 01 Apr 2016
Selecting Near-Optimal Learners via Incremental Data Allocation Ashish Sabharwal Horst Samulowitz Gerald Tesauro 84 64 0 31 Dec 2015
A PAC Approach to Application-Specific Algorithm Selection Rishi Gupta Tim Roughgarden 91 118 0 23 Nov 2015
Feature-Based Diversity Optimization for Problem Instance Classification Wanru Gao Samadhi Nallaperuma Frank Neumann 71 55 0 29 Oct 2015
A Topological Approach to Meta-heuristics: Analytical Results on the BFS vs. DFS Algorithm Selection Problem Tom Everitt Marcus Hutter 39 6 0 09 Sep 2015
Bayesian Additive Regression Trees using Bayesian Model Averaging B. Hernández A. Raftery S. Pennington Andrew C. Parnell 86 63 0 01 Jul 2015
Mondrian Forests for Large-Scale Regression when Uncertainty Matters Balaji Lakshminarayanan Daniel M. Roy Yee Whye Teh UQCV 116 56 0 11 Jun 2015
ASlib: A Benchmark Library for Algorithm Selection B. Bischl P. Kerschke Lars Kotthoff Marius Lindauer Y. Malitsky ... Holger Hoos Frank Hutter Kevin Leyton-Brown Kevin Tierney Joaquin Vanschoren 81 221 0 08 Jun 2015
The Configurable SAT Solver Challenge (CSSC) Frank Hutter Marius Lindauer A. Balint Sam Bayless Holger Hoos Kevin Leyton-Brown LRM 84 80 0 05 May 2015
Bayesian Optimization With Censored Response Data Frank Hutter Holger Hoos Kevin Leyton-Brown 92 36 0 07 Oct 2013