Sixth International Conference on Machine Learning and Applications (ICMLA 2007)最新文献_第4页

Constructive neural network ensemble for regression tasks in high dimensional spaces 高维空间回归任务的构造神经网络集成

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI: 10.1109/ICMLA.2007.82

A. Schmitz, H. Hefazi

引用次数: 8

Alignment of Multiple Proteins with an Ensemble of Hidden Markov Models 基于隐马尔可夫模型的多重蛋白质比对

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI: 10.1109/ICMLA.2007.90

Jia Song, Chunmei Liu, Yinglei Song, Junfeng Qu

{"title":"Alignment of Multiple Proteins with an Ensemble of Hidden Markov Models","authors":"Jia Song, Chunmei Liu, Yinglei Song, Junfeng Qu","doi":"10.1109/ICMLA.2007.90","DOIUrl":"https://doi.org/10.1109/ICMLA.2007.90","url":null,"abstract":"The alignment of multiple protein sequences is a problem of fundamental importance in bioinformatics. In general, the optimal alignment can be obtained through the optimization of an objective function. However, such an optimization task is often computationally intractible, most of the existing alignment tools thus use statistical or machine learning based methods to avoid direct optimizations. In this paper, we develop a new method that can progressively construct and update a set of alignments by adding sequences in certain order to each of the existing alignments. In particular, each of the existing alignments is modeled with a profile hidden markov model (HMM) and an added sequence is aligned to each of these profile HMMs. The profile HMMs in the set are then updated based on the alignments with leading alignment scores. We performed experiments on BaliBASE benchmarks to compare the performance of this new approach with that of other alignment tools. Our experiments showed that, by introducing an integer parameter that controls the number of profile HMMs in the set, we are able to efficiently explore the alignment space and significantly improve the alignment accuracy on sequences with low similarity.","PeriodicalId":448863,"journal":{"name":"Sixth International Conference on Machine Learning and Applications (ICMLA 2007)","volume":"05 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128983236","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: 8

Scalable optimal linear representation for face and object recognition 面向人脸和物体识别的可扩展最佳线性表示

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI: 10.1109/ICMLA.2007.110

Yiming Wu, Xiuwen Liu, W. Mio

{"title":"Scalable optimal linear representation for face and object recognition","authors":"Yiming Wu, Xiuwen Liu, W. Mio","doi":"10.1109/ICMLA.2007.110","DOIUrl":"https://doi.org/10.1109/ICMLA.2007.110","url":null,"abstract":"Optimal component analysis (OCA) is a linear method for feature extraction and dimension reduction. It has been widely used in many applications such as face and object recognitions. The optimal basis of OCA is obtained through solving an optimization problem on a Grassmann manifold. However, one limitation of OCA is the computational cost becoming heavy when the number of training data is large, which prevents OCA from efficiently applying in many real applications. In this paper, a scalable OCA (S-OCA) that uses a two-stage strategy is developed to bridge this gap. In the first stage, we cluster the training data using K-means algorithm and the dimension of data is reduced into a low dimensional space. In the second stage, OCA search is performed in the reduced space and the gradient is updated using an numerical approximation. In the process of OCA gradient updating, instead of choosing the entire training data, S-OCA randomly chooses a small subset of the training images in each class to update the gradient. This achieves stochastic gradient updating and at the same time reduces the searching time of OCA in orders of magnitude. Experimental results on face and object datasets show efficiency of the S-OCA method, in term of both classification accuracy and computational complexity.","PeriodicalId":448863,"journal":{"name":"Sixth International Conference on Machine Learning and Applications (ICMLA 2007)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124321749","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: 1

Model evaluation for prognostics: estimating cost saving for the end users 预测的模型评估:估计最终用户节省的成本

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI: 10.1109/ICMLA.2007.59

Chunsheng Yang, S. Létourneau

{"title":"Model evaluation for prognostics: estimating cost saving for the end users","authors":"Chunsheng Yang, S. Létourneau","doi":"10.1109/ICMLA.2007.59","DOIUrl":"https://doi.org/10.1109/ICMLA.2007.59","url":null,"abstract":"Unexpected failures of complex equipment such as trains or aircraft introduce superfluous costs, disrupt operation, have an effect on consumer's satisfaction, and potentially decrease safety in practice. One of the objectives of prognostics and health management (PHM) systems is to help reduce the number of unexpected failures by continuously monitoring the components of interest and predicting their failures sufficiently in advance to allow for proper planning. In other words, PHM systems may help turn unexpected failures into expected ones. Recent research has demonstrated the usefulness of data mining to help build prognostic models for PHM but also has identified the need for new model evaluation methods that take into account the specificities of prognostic applications. This paper investigates this problem. First, it reviews classical and recent methods to evaluate data mining models and it explains their deficiencies with respect to prognostic applications. The paper then proposes a novel approach that overcomes these deficiencies. This approach integrates the various costs and benefits involved in prognostics to quantify the cost saving expected from a given prognostic model. From the end user's perspective, the formula is practical as it is easy to understand and requires realistic inputs. The paper illustrates the usefulness of the methods through a real-world case study involving data-mining prognostic models and realistic costs/benefits information. The results show the feasibility of the approach and its applicability to various prognostic applications.","PeriodicalId":448863,"journal":{"name":"Sixth International Conference on Machine Learning and Applications (ICMLA 2007)","volume":"211 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115190579","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: 19

An OCR-independent character segmentation using shortest-path in grayscale document images 灰度文档图像中使用最短路径的字符分割

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI: 10.1109/ICMLA.2007.21

Jia Tse, Christopher Jones, Dean Curtis, E. Yfantis

引用次数: 28

Evolving kernel functions for SVMs by genetic programming 基于遗传规划的支持向量机核函数演化

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI: 10.1109/ICMLA.2007.70

L. Dioşan, A. Rogozan, J. Pécuchet

引用次数: 34

Combining multi-distributed mixture models and bayesian networks for semi-supervised learning 结合多分布混合模型和贝叶斯网络进行半监督学习

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI: 10.1109/ICMLA.2007.31

Manuel Stritt, L. Schmidt-Thieme, G. Poeppel

引用次数: 3

Discover the power of social and hidden curriculum to decision making: experiments with enron email and movie newsgroups 发现社会和隐藏课程对决策的力量:安然电子邮件和电影新闻组的实验

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI: 10.1109/ICMLA.2007.87

Hung-Ching Chen, M. Goldberg, M. Magdon-Ismail, W. Wallace

{"title":"Discover the power of social and hidden curriculum to decision making: experiments with enron email and movie newsgroups","authors":"Hung-Ching Chen, M. Goldberg, M. Magdon-Ismail, W. Wallace","doi":"10.1109/ICMLA.2007.87","DOIUrl":"https://doi.org/10.1109/ICMLA.2007.87","url":null,"abstract":"The power of social values that helps to surreptitiously shape or formulate our behavior patterns is not only inevitable, but also influential as the directions of our decision making can never seem to escape the impact of this hidden agent. Therefore, the search of such power agent can be validated through a machine learning approach that enables us to discover the agent dynamics in which drives the evolution of the social groups in a community. By doing so, we set up the problem by introducing a parameterized probabilistic model for the agent dynamics: the acts of an agent are determined by micro-laws with unknown parameters. Our approach is to identify the appropriate parameters in the model. To solve the problem, we develop heuristic expectation-maximization style algorithms for determining the micro-laws of a community based on either observed communication links between actors, or the observed evolution of social groups. We present the learning results from the synthetic data as well as the findings on real communities, e.g., Enron email and movie newsgroups.","PeriodicalId":448863,"journal":{"name":"Sixth International Conference on Machine Learning and Applications (ICMLA 2007)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128734859","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: 2

Enhanced recursive feature elimination 增强递归特征消除

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI: 10.1109/ICMLA.2007.35

Xue-wen Chen, Jong Cheol Jeong

引用次数: 136

Tracking recurrent concept drift in streaming data using ensemble classifiers 使用集成分类器跟踪流数据中的循环概念漂移

Sixth International Conference on Machine Learning and Applications (ICMLA 2007) Pub Date : 2007-12-13 DOI: 10.1109/ICMLA.2007.109

S. Ramamurthy, R. Bhatnagar

引用次数: 91