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检索条件"主题词=algorithm selection"
316 条 记 录,以下是11-20 订阅
A review on preprocessing algorithm selection with meta-learning
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KNOWLEDGE AND INFORMATION SYSTEMS 2024年 第1期66卷 1-28页
作者: Pio, Pedro B. Rivolli, Adriano de Carvalho, Andre C. P. L. F. Garcia, Luis P. F. Univ Brasilia UnB Dept Comp Sci CIC BR-70910900 Brasilia DF Brazil Fed Univ Technol UTFPR Campus Cornelio Procopio BR-86300000 Cornelio Procopio Parana Brazil Univ Sao Paulo Inst Math & Comp Sci ICMC Ave Trabalhador Sao Carlense 400 BR-13560970 Sao Carlos SP Brazil
Several AutoML tools aim to facilitate the usability of machine learning algorithms, automatically recommending algorithms using techniques such as meta-learning, grid search, and genetic programming. However, the pre... 详细信息
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algorithm selection and instance space analysis for curriculum-based course timetabling
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JOURNAL OF SCHEDULING 2022年 第1期25卷 35-58页
作者: De Coster, Arnaud Musliu, Nysret Schaerf, Andrea Schoisswohl, Johannes Smith-Miles, Kate TU Wien Inst Log & Computat Database & Artificial Intelligence Grp Vienna Austria TU Wien Christian Doppler Lab Artificial Intelligence & O Vienna Austria Univ Udine DPIA Udine Italy Univ Melbourne Sch Math & Stat Melbourne Vic Australia
We propose an algorithm selection approach and an instance space analysis for the well-known curriculum-based course timetabling problem (CB-CTT), which is an important problem for its application in higher education.... 详细信息
来源: 评论
Landscape features in single-objective continuous optimization: Have we hit a wall in algorithm selection generalization?
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SWARM AND EVOLUTIONARY COMPUTATION 2025年 94卷
作者: Cenikj, Gjorgjina Petelin, Gasper Seiler, Moritz Cenikj, Nikola Eftimov, Tome Jozef Stefan Inst Comp Syst Dept Ljubljana 1000 Slovenia Jozef Stefan Int Postgrad Sch Ljubljana 1000 Slovenia Paderborn Univ D-33098 Paderborn Germany Tech Univ Munich D-80333 Munich Germany
The process of identifying the most suitable optimization algorithm fora specific problem, referred to as algorithm selection (AS), entails training models that leverage problem landscape features to forecast algorith... 详细信息
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Hybrid algorithm selection and Hyperparameter Tuning on Distribute Machine Learning Resources: Hierarchical Agent-based Approach
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ACM TRANSACTIONS ON INTERNET TECHNOLOGY 2024年 第4期24卷 1-30页
作者: Esmaeili, Ahmad Rayz, Julia Matson, Eric Wichita State Univ Sch Comp Wichita KS 67260 USA Purdue Univ Comp & Informat Technol W Lafayette IN USA
algorithm selection and hyperparameter tuning are critical steps in both academic and applied machine learning (ML). These steps are becoming increasingly delicate due to the extensive rise in the number, diversity, a... 详细信息
来源: 评论
Meta-learning from learning curves for budget-limited algorithm selection
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PATTERN RECOGNITION LETTERS 2024年 185卷 225-231页
作者: Nguyen, Manh Hung Hosoya, Lisheng Sun Guyon, Isabelle Chalearn Berkeley CA 94708 USA Google Res Mountain View CA USA Univ Paris Saclay LISN Gif Sur Yvette France
Training a large set of machine learning algorithms to convergence in order to select the best-performing algorithm for a dataset is computationally wasteful. Moreover, in a budget-limited scenario, it is crucial to c... 详细信息
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Deep Reinforcement Learning for Dynamic algorithm selection: A Proof-of-Principle Study on Differential Evolution
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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2024年 第7期54卷 4247-4259页
作者: Guo, Hongshu Ma, Yining Ma, Zeyuan Chen, Jiacheng Zhang, Xinglin Cao, Zhiguang Zhang, Jun Gong, Yue-Jiao South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Natl Univ Singapore Coll Design & Engn Dept Ind Syst Engn & Management Singapore Singapore Singapore Management Univ Sch Comp & Informat Syst Singapore Singapore Nankai Univ Tianjin 300192 Peoples R China Hanyang Univ Seoul 04763 South Korea Univ Victoria Melbourne Vic 3004 Australia
Evolutionary algorithms, such as differential evolution, excel in solving real-parameter optimization challenges. However, the effectiveness of a single algorithm varies across different problem instances, necessitati... 详细信息
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A study on the effects of normalized TSP features for automated algorithm selection
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THEORETICAL COMPUTER SCIENCE 2023年 第PartB期940卷 123-145页
作者: Heins, Jonathan Bossek, Jakob Pohl, Janina Seiler, Moritz Trautmann, Heike Kerschke, Pascal Big Data Analyt Transportat TU Dresden Dresden Germany Rhein Westfal TH Aachen Methodol Aachen Germany Univ Munster Stat & Optimizat Munster Germany
Classic automated algorithm selection (AS) for (combinatorial) optimization problems heavily relies on so-called instance features, i.e., numerical characteristics of the problem at hand ideally extracted with computa... 详细信息
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When algorithm selection meets Bi-linear Learning to Rank: accuracy and inference time trade off with candidates expansion
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INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS 2023年 第2期16卷 173-189页
作者: Yuan, Jing Geissler, Christian Shao, Weijia Lommatzsch, Andreas Jain, Brijnesh Tech Univ Berlin TEL-14Ernst Reuter Pl 7 D-10587 Berlin Germany
algorithm selection (AS) tasks are dedicated to find the optimal algorithm for an unseen problem instance. With the knowledge of problem instances' meta-features and algorithms' landmark performances, Machine ... 详细信息
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Automated algorithm selection: from Feature-Based to Feature-Free Approaches
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JOURNAL OF HEURISTICS 2023年 第1期29卷 1-38页
作者: Alissa, Mohamad Sim, Kevin Hart, Emma Edinburgh Napier Univ Sch Comp Edinburgh Scotland
We propose a novel technique for algorithm-selection, applicable to optimisation domains in which there is implicit sequential information encapsulated in the data, e.g., in online bin-packing. Specifically we train t... 详细信息
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Recommender Systems algorithm selection for Ranking Prediction on Implicit Feedback Datasets  24
Recommender Systems Algorithm Selection for Ranking Predicti...
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18h ACM Conference on Recommender Systems (RecSys)
作者: Wegmeth, Lukas Vente, Tobias Beel, Joeran Univ Siegen Intelligent Syst Grp Siegen Germany
The recommender systems algorithm selection problem for ranking prediction on implicit feedback datasets is under-explored. Traditional approaches in recommender systems algorithm selection focus predominantly on rati... 详细信息
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