2009 IEEE International Conference on Data Mining Workshops最新文献_第2页

Spatio-temporal Multi-dimensional Relational Framework Trees 时空多维关系框架树

2009 IEEE International Conference on Data Mining Workshops Pub Date : 2009-12-06 DOI: 10.1109/ICDMW.2009.95

Matthew Bodenhamer, Samuel Bleckley, Daniel Fennelly, A. Fagg, A. McGovern

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引用次数: 7

Efficient Dense Structure Mining Using MapReduce 基于MapReduce的高效密集结构挖掘

2009 IEEE International Conference on Data Mining Workshops Pub Date : 2009-12-06 DOI: 10.1109/ICDMW.2009.48

Shengqi Yang, Bai Wang, Haizhou Zhao, Bin Wu

引用次数: 26

Probabilistic Labeled Semi-supervised SVM 概率标记半监督支持向量机

2009 IEEE International Conference on Data Mining Workshops Pub Date : 2009-12-06 DOI: 10.1109/ICDMW.2009.14

Mingjie Qian, F. Nie, Changshui Zhang

引用次数: 6

HOCT: A Highly Scalable Algorithm for Training Linear CRF on Modern Hardware HOCT:一种在现代硬件上训练线性CRF的高度可扩展算法

2009 IEEE International Conference on Data Mining Workshops Pub Date : 2009-12-06 DOI: 10.1109/ICDMW.2009.69

Tianyuan Chen, Lei Chang, Jianqing Ma, Wei Zhang, Feng Gao

引用次数: 0

Nonsmooth Bilevel Programming for Hyperparameter Selection 超参数选择的非光滑双层规划

2009 IEEE International Conference on Data Mining Workshops Pub Date : 2009-12-06 DOI: 10.1109/ICDMW.2009.74

Gregory M. Moore, Charles Bergeron, Kristin P. Bennett

{"title":"Nonsmooth Bilevel Programming for Hyperparameter Selection","authors":"Gregory M. Moore, Charles Bergeron, Kristin P. Bennett","doi":"10.1109/ICDMW.2009.74","DOIUrl":"https://doi.org/10.1109/ICDMW.2009.74","url":null,"abstract":"We propose a nonsmooth bilevel programming method for training linear learning models with hyperparameters optimized via $T$-fold cross-validation (CV). This algorithm scales well in the sample size. The method handles loss functions with embedded maxima such as in support vector machines. Current practice constructs models over a predefined grid of hyperparameter combinations and selects the best one, an inefficient heuristic. Innovating over previous bilevel CV approaches, this paper represents an advance towards the goal of self-tuning supervised data mining as well as a significant innovation in scalable bilevel programming algorithms. Using the bilevel CV formulation, the lower-level problems are treated as unconstrained optimization problems and are replaced with their optimality conditions. The resulting nonlinear program is nonsmooth and nonconvex. We develop a novel bilevel programming algorithm to solve this class of problems, and apply it to linear least-squares support vector regression having hyperparameters $C$ (tradeoff) and $epsilon$ (loss insensitivity). This new approach outperforms grid search and prior smooth bilevel CV methods in terms of modeling performance. Increased speed foresees modeling with an increased number of hyperparameters.","PeriodicalId":351078,"journal":{"name":"2009 IEEE International Conference on Data Mining Workshops","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121267959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Compressed Spectral Clustering 压缩光谱聚类

2009 IEEE International Conference on Data Mining Workshops Pub Date : 2009-12-06 DOI: 10.1109/ICDMW.2009.22

Bin Zhao, Changshui Zhang

引用次数: 4

A Study of Language Model for Image Retrieval 图像检索的语言模型研究

2009 IEEE International Conference on Data Mining Workshops Pub Date : 2009-12-06 DOI: 10.1109/ICDMW.2009.114

Bo Geng, Linjun Yang, Chao Xu

引用次数: 16

TubeTagger - YouTube-based Concept Detection TubeTagger -基于youtube的概念检测

2009 IEEE International Conference on Data Mining Workshops Pub Date : 2009-12-06 DOI: 10.1109/ICDMW.2009.41

A. Ulges, Markus Koch, Damian Borth, T. Breuel

引用次数: 19

Kernel K-means Based Framework for Aggregate Outputs Classification 基于核k均值的汇总输出分类框架

2009 IEEE International Conference on Data Mining Workshops Pub Date : 2009-12-06 DOI: 10.1109/ICDMW.2009.33

Shuo Chen, Bin Liu, Mingjie Qian, Changshui Zhang

引用次数: 24

Improved Multi Label Classification in Hierarchical Taxonomies 层次分类法中改进的多标签分类

2009 IEEE International Conference on Data Mining Workshops Pub Date : 2009-12-06 DOI: 10.1109/ICDMW.2009.110

Kunal Punera, Suju Rajan

引用次数: 3