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检索条件"机构=Department of Data Science and Machine Learning Computer Science"
3616 条 记 录,以下是3351-3360 订阅
Trajectory-Based Short-Sighted Probabilistic Planning  12
Trajectory-Based Short-Sighted Probabilistic Planning
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Annual Conference on Neural Information Processing Systems
作者: Felipe W. Trevizan Manuela M. Veloso Machine Learning Department Carnegie Mellon University - Pittsburgh PA Computer Science Department Carnegie Mellon University - Pittsburgh PA
Probabilistic planning captures the uncertainty of plan execution by probabilistically modeling the effects of actions in the environment, and therefore the probability of reaching different states from a given state ...
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Assessing reliability of protein-protein interactions by gene ontology integration
Assessing reliability of protein-protein interactions by gen...
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IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology (CIBCB)
作者: George D. Montañez Young-Rae Cho Machine Learning Department Carnegie Mellon University Pittsburgh PA USA Department of Computer Science Baylor University Waco TX USA
Recent advances in genome-wide identification of protein-protein interactions (PPIs) have produced an abundance of interaction data which give an insight into functional associations among proteins. However, it is kno... 详细信息
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Slice sampling normalized kernel-weighted completely random measure mixture models  12
Slice sampling normalized kernel-weighted completely random ...
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Annual Conference on Neural Information Processing Systems
作者: Nicholas J.Foti Sinead A. Williamson Department of Computer Science Dartmouth College Hanover NH 03755 Department of Machine Learning Carnegie Mellon University Pittsburgh PA 15213
A number of dependent nonparametric processes have been proposed to model non-stationary data with unknown latent dimensionality. However, the inference algorithms are often slow and unwieldy, and are in general highl...
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Generalized spike-and-slab priors for Bayesian group feature selection using expectation propagation
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The Journal of machine learning Research 2013年 第1期14卷
作者: Kevin Murphy Bernhard Schölkopf Daniel Hernández-Lobato José Miguel Hernández-Lobato Pierre Dupont Google MPI for Intelligent Systems Computer Science Department Universidad Autónoma de Madrid Madrid Spain Department of Engineering University of Cambridge Cambridge United Kingdom Machine Learning Group ICTEAM Université Catholique de Louvain Louvain-la-Neuve Belgium
We describe a Bayesian method for group feature selection in linear regression problems. The method is based on a generalized version of the standard spike-and-slab prior distribution which is often used for individua... 详细信息
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Sparse LS-SVM two-steps model selection method
Sparse LS-SVM two-steps model selection method
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International Conference on machine learning and Cybernetics (ICMLC)
作者: Binbin Sun Daniel S. Yeung Department of Computer Science Shenzhen Graduated School Harbin Institute of Technology China Machine Learning and Cybernetics Research Center School of Computer Science and Engineering South China University of Technology China
Least Square Support Vector machine (LS-SVM) converts the hinge loss function of SVM into a least square loss function which simplified the original quadratic programming training method to a linear system solving pro... 详细信息
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Exponential concentration for mutual information estimation with application to forests
Exponential concentration for mutual information estimation ...
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26th Annual Conference on Neural Information Processing Systems 2012, NIPS 2012
作者: Liu, Han Lafferty, John Wasserman, Larry Department of Operations Research and Financial Engineering Princeton University NJ 08544 United States Department of Computer Science University of Chicago IL 60637 United States Department of Statistics University of Chicago IL 60637 United States Department of Statistics United States Machine Learning Department Carnegie Mellon University PA 15231 United States
We prove a new exponential concentration inequality for a plug-in estimator of the Shannon mutual information. Previous results on mutual information estimation only bounded expected error. The advantage of having the... 详细信息
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Taming the Reservoir: Feedforward Training for Recurrent Neural Networks
Taming the Reservoir: Feedforward Training for Recurrent Neu...
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International Joint Conference on Neural Networks
作者: Oliver Obst Martin Riedmiller Commonwealth Scientific and Industrial Research Organisation ICT Centre Adaptive Systems University of Freiburg Department of Computer Science Machine Learning Lab
Recurrent neural networks are successfully used for tasks like time series processing and system identification. Many of the approaches to train these networks, however, are often regarded as too slow, too complicated... 详细信息
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Projection Retrieval for Classification  12
Projection Retrieval for Classification
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Annual Conference on Neural Information Processing Systems
作者: Madalina Fiterau Artur Dubrawski Machine Learning Department Carnegie Mellon University Pittsburgh PA 15213 School of Computer Science Carnegie Mellon University Pittsburgh PA 15213
In many applications, classification systems often require human intervention in the loop. In such cases the decision process must be transparent and comprehensible, simultaneously requiring minimal assumptions on the... 详细信息
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Evaluating Relational Ranking Queries Involving Both Text Attributes and Numeric Attributes
Evaluating Relational Ranking Queries Involving Both Text At...
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Conference on computer science and Software Engineering(CSSE 2012)
作者: Liang Zhu Zhaoliang Xie Qin Ma Key Laboratory of Machine Learning and Computational Intelligence School of Mathematics and Computer ScienceHebei University Department of Foreign Language Teaching and Research Hebei University
In many database applications, ranking queries may reference both text and numeric attributes, where the ranking functions are based on both semantic distances/similarities for text attributes and numeric distances fo... 详细信息
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Chinese Keyword Search by Indexing in Relational databases
Chinese Keyword Search by Indexing in Relational Databases
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Conference on computer science and Software Engineering(CSSE 2012)
作者: Liang Zhu Lijuan Pan Qin Ma Key Laboratory of Machine Learning and Computational Intelligence School of Mathematics and Computer ScienceHebei University Department of Foreign Language Teaching and Research Hebei University
In this paper, we propose a new method based on index to realize IR-style Chinese keyword search with ranking strategies in relational databases. This method creates an index by using the related information of tuple ... 详细信息
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