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检索条件"主题词=algorithm selection"
313 条 记 录,以下是251-260 订阅
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Selecting algorithms for the Quadratic Assignment Problem with a Multi-label Meta-learning Approach
Selecting Algorithms for the Quadratic Assignment Problem wi...
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7th Brazilian Conference on Intelligent Systems (BRACIS)
作者: Dantas, Augusto Lopez Ramirez Pozo, Aurora Trinidad Univ Fed Parana Dept Comp Sci Curitiba Parana Brazil
Meta-heuristic algorithms have been used to obtain feasible solutions in reasonable time for many NP-hard search problems. However, the performance of the algorithms heavily depends on the features of the problem. So,... 详细信息
来源: 评论
An experimental evaluation of data mining algorithms using hyperparameter optimization  14
An experimental evaluation of data mining algorithms using h...
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14th Mexican International Conference on Artificial Intelligence (MICAI)
作者: Marques, Rayrone Z. N. Coutinho, Luciano R. Borchartt, Tiago B. Vale, Samyr B. Silva, Francisco J. S. Univ Fed Maranhao Dept Informat Postgrad Program Comp Sci Sao Luis MA Brazil
The challenge to choose the best algorithm and its best parameters for a given problem is known as Combined algorithm selection and Hyperparameter Optimization Problem. Among all the classification algorithms availabl... 详细信息
来源: 评论
Auto-Surprise: An Automated Recommender-System (AutoRecSys) Library with Tree of Parzens Estimator (TPE) Optimization  20
Auto-Surprise: An Automated Recommender-System (AutoRecSys) ...
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14th ACM Conference on Recommender Systems (RECSYS)
作者: Anand, Rohan Beel, Joeran Trinity Coll Dublin Dublin Ireland
We introduce Auto-Surprise(1), an automated recommender system library. Auto-Surprise is an extension of the Surprise recommender system library and eases the algorithm selection and configuration process. Compared to... 详细信息
来源: 评论
Improving Recommender Systems Through the Automation of Design Decisions  23
Improving Recommender Systems Through the Automation of Desi...
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17th ACM Conference on Recommender Systems (RecSys)
作者: Wegmeth, Lukas Univ Siegen Siegen Germany
Recommender systems developers are constantly faced with difficult design decisions. Additionally, the number of options that a recommender systems developer has to consider continually grows over time with new innova... 详细信息
来源: 评论
Towards Automated Configuration of Stream Clustering algorithms  19th
Towards Automated Configuration of Stream Clustering Algorit...
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European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)
作者: Carnein, Matthias Trautmann, Heike Bifet, Albert Pfahringer, Bernhard Univ Munster Munster Germany Univ Waikato Hamilton New Zealand
Clustering is an important technique in data analysis which can reveal hidden patterns and unknown relationships in the data. A common problem in clustering is the proper choice of parameter settings. To tackle this, ... 详细信息
来源: 评论
Performance Issues in Evaluating Models and Designing Simulation algorithms
Performance Issues in Evaluating Models and Designing Simula...
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International Workshop on High Performance Computational Systems Biology (HiBi 2009)
作者: Ewald, Roland Himmelspach, Jan Jeschke, Matthias Leye, Stefan Uhrmacher, Adelinde M. Univ Rostock Inst Comp Sci Rostock Germany
The increase and diversity of simulation methods bears witness of the need for more efficient discrete event simulations in computational biology - but how efficient are those methods. and how to ensure all efficient ... 详细信息
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Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems  8
Improved Automated CASH Optimization with Tree Parzen Estima...
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8th IEEE International Conference on Data Science and Advanced Analytics (DSAA)
作者: Duc Anh Nguyen Kong, Jiawen Wang, Hao Menzel, Stefan Sendhoff, Bernhard Kononova, Anna, V Baeck, Thomas Leiden Univ Leiden Inst Adv Comp Sci LIACS Leiden Netherlands Honda Res Inst Europe GmbH HRI EU Offenbach Germany
The imbalanced classification problem is very relevant in both academic and industrial applications. The task of finding the best machine learning model to use for a specific imbalanced dataset is complicated due to a... 详细信息
来源: 评论
Benchmarking algorithm Portfolio Construction Methods  22
Benchmarking Algorithm Portfolio Construction Methods
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Genetic and Evolutionary Computation Conference (GECCO)
作者: Munoz, Mario Andres Soleimani, Hamed Kandanaarachchi, Sevvandi Univ Melbourne Sch Math & Stat Parkville Vic Australia RMIT Univ Sch Sci Melbourne Vic Australia
A portfolio is a set of algorithms, which run concurrently or interchangeably, whose aim is to improve performance by avoiding a bad selection of a single algorithm. Despite its high error tolerance, a carefully const... 详细信息
来源: 评论
One-Class Classification for Selecting Synthetic Datasets in Meta-Learning
One-Class Classification for Selecting Synthetic Datasets in...
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International Joint Conference on Neural Networks (IJCNN) held as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)
作者: Parente, Regina R. Prudencio, Ricardo B. C. Univ Fed Pernambuco UFPE Ctr Informat CIn Recife PE Brazil
algorithm selection is a challenging task in machine learning. Meta-learning treats algorithm selection as a supervised learning task, in which training examples (i.e., meta examples) are generated from experiments pe... 详细信息
来源: 评论
Using Result Profiles to Drive Meta-learning  18th
Using Result Profiles to Drive Meta-learning
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18th European, Mediterranean, and Middle Eastern Conference on Information Systems (EMCIS)
作者: Grabczewski, Krzysztof Nicolaus Copernicus Univ Inst Engn & Technol Fac Phys Astron & Informat Ul Grudziadzka 5 PL-87100 Torun Poland
Knowledge gained by meta-learning processes is valuable when it can be successfully used in solving algorithm selection problems. There is still strong need for automated tools for learning from data, performing model... 详细信息
来源: 评论