[PDF] Top 20 A Parameter-Free Classification Method for Large Scale Learning
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A Parameter-Free Classification Method for Large Scale Learning
... MODL method and the unsu- pervised equal frequency method with 10 intervals, as a ...MODL method selects a discretization having one single interval, leading to the elimination of the ...MODL ... See full document
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Large Scale Multiple Kernel Learning
... machine learning toolbox which contains a modified version of SVM light (Joachims, 1999) on 500, 1, 000, 5,000, 10,000, 30,000, 50,000, 100,000, 200, 000, 500, 000, 1,000,000, 2, 000,000, 5,000,000 and 10, 000, ... See full document
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Semi Supervised Learning with Auxiliary Evaluation Component for Large Scale e Commerce Text Classification
... ing method to utilize unlabeled data and user feedback signals to improve the per- formance of ML ...The method employs a primary model M ain and an auxiliary evaluation model Eval, where M ain and Eval ... See full document
9
Large Scale Online Kernel Learning
... higher learning time cost for all the budget online kernel learning ...is large enough, further increasing the budget size has limited gain on the improvement of classification ...size ... See full document
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Large-scale SVD and Manifold Learning
... machine learning tasks. In fact, the Nystr¨om method has been shown to be successful on a variety of learning tasks including Support Vector Machines (Fine and Scheinberg, 2002), Gaussian Processes ... See full document
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A Method of Point Cloud Classification Using Multi scale Dimensionality Features and Transductive Learning
... and large detection range ...data classification is a kind of widely used processing mode in environmental perception and it is usually used for the pre-processing ... See full document
8
Evaluation of Takagi-Sugeno-Kang fuzzy method in entropy-based detection of DDoS attacks
... from 20 to 150. There are 40 servers in the local network, of which one is the attack target. The topology is an unbalanced dumbbell topology, illustrated in Fig. 5. The attack target is part of the server tree. This ... See full document
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Filtering large-scale event collections using a combination of supervised and unsupervised learning for event trigger classification
... this method produced only an increase of ...on large-scale resources such as EVEX are significant: hundreds of thousands of false events can be excluded, thus greatly improving the quality of the ... See full document
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PestNet : an end-to-end deep learning approach for large-scale multi-class pest detection and classification
... machine learning methods aim to address multi- class pest detection issue that focuses more on pest localization which is much more difficult than ...deep learning has made an obvious breakthrough on ... See full document
12
The Study of the Large Scale Twitter on Machine Learning
... machine learning framework consists of two components: a core Java library and a layer of lightweight wrappers that expose functionalities in ...classify method, which takes as input a feature vector and ... See full document
5
Revisiting the Nystr{\"{o}m} Method for Improved Large-scale Machine Learning
... by large-scale data analysis and machine learning applications, recent theoretical and empirical work has focused on “sketching” methods such as random sampling and random projection ...A ... See full document
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Learning Taxonomy Adaptation in Large-scale Classification
... text classification has been studied by Koller and Sahami (1997) and Dumais and Chen ...manner. Parameter smoothing for Naive Bayes classifier along the root to leaf path was explored by McCallum et ...the ... See full document
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A Meta-Top-Down Method for Large-Scale Hierarchical Classification
... Meta learning is a subfield of Machine learning where automatic learning algorithms are applied on meta-data about machine learning ...automatic learning can become flexible in solving ... See full document
5
Continuous Learning for Large scale Personalized Domain Classification
... Domain classification is the task of mapping spo- ken language utterances to one of the NLU do- mains in IPDAs. A straightforward solution to tackle this problem is to ask users to explicitly mention the domain ... See full document
11
Emergence of large cliques in random scale free networks
... The occurrence of a skewed degree distribution has also striking consequences regarding the frequency of partic- ular subgraphs present in the network. For example, ER graphs with finite average connectivity have a ... See full document
9
A Doppler aliasing free micro motion parameter estimation method in the terahertz band
... this reference curve the matching curve (Fig. 5a). Their shapes are match well with each other, and the values of matching pixels are larger, the average value of matching pixels is larger, too. If we map the mean of all ... See full document
9
Large scale Analysis of Spoken Free verse Poetry
... machine learning tasks may be outstanding and important in our ...machine learning approaches which rely on the repetition with small deviation of training ... See full document
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Enhance Top down method with Meta Classification for Very Large scale Hierarchical Classification
... the method of selecting label candidates is kind of like a classification method as both of them take in samples and give out the labels most likely to be ...the method of selecting la- bel ... See full document
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On Efficient Large Margin Semisupervised Learning: Method and Theory
... a large margin semisupervised learning method, which aims to extract the information from unlabeled data for estimating the Bayes decision ...proposed method, using both the grouping ... See full document
24
Large Scale Machine Learning on Debugging Machine Learning Systems
... As utilized in daily language, “learning” is really a really wide expression that indicates the getting of understanding, talent and knowledge from training, knowledge or reflection. For the applications of ... See full document
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