搜索结果: 1-11 共查到“统计学 Machine Learning”相关记录11条 . 查询时间(0.078 秒)
A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance
convex optimization minimax theorem robust optimization
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2015/7/9
This paper concerns a fractional function of the form x^Ta/sqrt{x^TBx}, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, and choosing (a,B)...
Statistical Model Building, Machine Learning, and the Ah-Ha Moment
Statistical Model Building Machine Learning the Ah-Ha Moment
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2013/4/28
The Committee of Presidents of Statistical Societies (COPSS) will celebrate its 50th Anniversary in 2013. As part of its celebration, COPSS intends to publish a book with contributions from the past r...
Relevance As a Metric for Evaluating Machine Learning Algorithms
Machine learning algorithms performance metric proba-bilistic approach
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2013/4/28
In machine learning, the choice of a learning algorithm that is suitable for the application domain is critical. The performance metric used to compare different algorithms must also reflect the conce...
On Sparsity Inducing Regularization Methods for Machine Learning
Sparsity Inducing Regularization Methods for Machine Learning
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2013/5/2
During the past years there has been an explosion of interest in learning methods based on sparsity regularization. In this paper, we discuss a general class of such methods, in which the regularizer ...
Machine Learning for Bioclimatic Modelling
Machine Learning Bioclimatic Modelling Geographic Range Artificial Neural Network Evolutionary Algorithm
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2013/5/2
Many machine learning (ML) approaches are widely used to generate bioclimatic models for prediction of geographic range of organism as a function of climate. Applications such as prediction of range s...
Common Mistakes when Applying Computational Intelligence and Machine Learning to Stock Market modelling
Computational intelligence machine learning stock market equities automated stock tradin mistakes.
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2012/9/17
For a number of reasons, computational intelligence and machine learning methods have been largely dismissed by the professional community. The reasons for this are numerous and ...
ProDiGe: PRioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples
ProDiGe PRioritization Disease Genes multitask machine learning positive unlabeled examples
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2011/7/6
Elucidating the genetic basis of human diseases is a central goal of genetics and molecular biology. While traditional linkage analysis and modern high-throughput techniques often provide long lists o...
Identifying Hosts of Families of Viruses: A Machine Learning Approach
viral host machine learning adaboost alternating decision tree mismatch k-mers
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2011/6/21
Identifying viral pathogens and characterizing their transmission is essential to developing effective
public health measures in response to a pandemic. Phylogenetics, though currently the most popul...
Self-configuration from a Machine-Learning Perspective
Machine-Learning Perspective Self-configuration Sequen-tial Parameter Optimization
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2011/6/21
The goal of machine learning is to provide solutions which are trained by data
or by experience coming from the environment. Many training algorithms exist and
some brilliant successes were achieved...
Kernel methods in machine learning
Machine learning reproducing kernels support vector machines graphical models
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2010/4/26
We review machine learning methods employing positive definite
kernels. These methods formulate learning and estimation problems
in a reproducing kernel Hilbert space (RKHS) of functions defined
on...
Machine Learning Department（ML）at Carnegie Mellon University（图）
ML Machine Learning Department at Carnegie Mellon University 统计学 机械学 计算机基础科学
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2007/12/24
The Machine Learning Department is an academic department within Carnegie Mellon University's School of Computer Science. We focus on research and education in all areas of statistical machine learnin...