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http://www.cl.cam.ac.uk/~av308/vlachos_msc_thesis.pdf
annotation cost. Typically, the selections for active learning are made by a machine learning method which determines the informativity of the examples. In this thesis, the machine learning method used for active learning is support vector ma-chines (SVMs). This method has significant theoretical advantages and it has shown impres-
https://onlinelibrary.wiley.com/doi/abs/10.1002/widm.1132
Honghuang Lin and Peng Li, Circuit Performance Classification With Active Learning Guided Sampling for Support Vector Machines, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 34, 9, (1467), (2015).Cited by: 63
https://doi.org/10.3233/IDA-173496
Active learning has proven to be quite effective in a vast array of machine learning tasks. Despite the lower labeling cost of active learning, it has been shown that active learning still can not reach state-of-the-art performance on several classifCited by: 1
http://image.diku.dk/jank/papers/WIREs2014.pdf
3 Support Vector Machine Support vector machines (SVMs) are state-of-the-art classifiers [6, 12, 26, 36, 38, 40]. They have proven to provide well-generalizing solutions in practice and are well understood theoretically [42]. The kernel trick [38] allows for an easy handling of …
https://www.youtube.com/watch?v=ztCXSAUAe38
Dec 13, 2013 · Brief tutorial on active learning for support vector machines. Based on: S. Tong and D. Koller (2001). "Support vector machine active learning with applications to text classification." Journal of ...Author: Shayan Doroudi
https://www.researchgate.net/publication/2430239_Less_is_More_Active_Learning_with_Support_Vector_Machines
We describe a simple active learning heuristic which greatly enhances the generalization behavior of support vector machines (SVMs) on several practical document classification tasks.
https://ai.stanford.edu/~koller/Papers/Tong+Koller:ICML00.pdf
Support vector machines have met with signif-icant success in numerous real-world learning tasks. However, like most machine learning al-gorithms, they are generally applied using a ran-domly selected training set classified in advance. In many settings, we also have the option of us-ing pool-based active learning. Instead of using
http://courses.cms.caltech.edu/cs101.2/slides/cs101.2-09-svm-active-learning.pdf
SUPPORT VECTOR MACHINE ACTIVE LEARNING CS 101.2 Caltech, 03 Feb 2009 Paper by S. Tong, D. Koller Presented by Krzysztof Chalupka
http://wexler.free.fr/library/files/schohn%20%282000%29%20less%20is%20more.%20active%20learning%20with%20support%20vector%20machines.pdf
the process of active learning, and briefly review our target learning architecture, the support vector machine. Section 2 discusses several active learning heuristics for support vector machines. Sections 3 and 4 describe a se-ries of experiments and results with one of those heuristics. We consider the implications of our results in Section 5.
http://jmlr.org/papers/volume2/tong01a/tong01a.pdf
Support vector machines have met with significant success in numerous real-world learning tasks. However, like most machine learning algorithms, they are generally applied using a randomly selected training set classified in advance. In many settings, we also have the option ofusingpool-based active learning. Instead ofusing a randomly ...
https://onlinelibrary.wiley.com/doi/pdf/10.1002/widm.1132
Support vector machine (SVM) classifiers are particularly well‐suited for active learning due to their convenient mathematical properties. They perform linear classification, typically in a kernel‐induced feature space, which makes expressing the distance of a …
http://www.cs.cmu.edu/%7Eninamf/courses/601sp15/slides/18_svm-ssl_03-25-2015.pdf
• Support Vector Machines (SVMs). • Semi-Supervised SVMs. ... algorithms in machine learning. Support Vector Machines (SVMs). Directly motivated by Margins and Kernels! Geometric Margin Definition: The margin of example w.r.t. a linear sep. is the ... Active Learning face O O O Expert Labeler raw data Classifier not face
https://www.researchgate.net/publication/265016888_Active_learning_with_support_vector_machines
The proposed methodology combines a low-discrepancy sequence (Sobol) and a support vector machine (SVM) in an active learning procedure able to efficiently and accurately estimate the …
https://content.iospress.com/articles/intelligent-data-analysis/ida173496
As shown in Fig. 1, active learning is mainly composed of learning algorithm and select machine, where learning algorithm is supervised learning method, such as support vector machines (SVM), and select machine is used to select data samples during each iteration according to uncertainty sampling [].During active learning process, learning algorithm first obtains an initial model from existing ...
https://link.springer.com/chapter/10.1007/978-3-662-44848-9_14
Abstract. Margin-based strategies and model change based strategies represent two important types of strategies for active learning. While margin-based strategies have been dominant for Support Vector Machines (SVMs), most methods are based on heuristics and lack a solid theoretical support.
https://arxiv.org/pdf/1801.07875.pdf
3) support vector machines (SVMs) are able to train high-performing systems for the application. Two examples of such applications are Text Classification (TC) and Relation Extraction (RE). Characteristics 2 and 3 suggest the use of AL-SVM (Active Learning (AL) with Support Vector Machines…
https://link.springer.com/chapter/10.1007%2F978-3-540-72584-8_148
Abstract. In this paper, active learning with support vector machines (SVMs) is applied to the problem of tornado prediction. This method is used to predict which storm-scale circulations yield tornadoes based on the radar derived Mesocyclone Detection Algorithm (MDA) …
http://wexler.free.fr/library/files/schohn%20%282000%29%20less%20is%20more.%20active%20learning%20with%20support%20vector%20machines.pdf
the process of active learning, and briefly review our target learning architecture, the support vector machine. Section 2 discusses several active learning heuristics for support vector machines. Sections 3 and 4 describe a se-ries of experiments and results with one of those heuristics. We consider the implications of our results in Section 5.
https://www.aaai.org/Papers/ICML/2003/ICML03-011.pdf
properties of support vector machines that are relevant in the field of active learning. In the first part of sec-tion 3, we discuss previous approaches to active learn-ing with support vector machines, while the second part introduces our new selection strategy. Section 5 shows experimental results supporting the efficiency of our strategy.
https://dl.acm.org/citation.cfm?id=944793
Support vector machines have met with significant success in numerous real-world learning tasks. However, like most machine learning algorithms, they are generally applied using a randomly selected training set classified in advance.
https://www.sciencedirect.com/science/article/pii/S0031320312001550
Besides, since active learning is favorably applied to support vector machine (SVM) and its related applications, the strategy is further restricted to a specific algorithm called inconsistency-based active learning for SVM (I-ALSVM).
https://arxiv.org/abs/1610.03995
Oct 13, 2016 · In addition, many existing AL techniques pay too little attention to their practical applicability. To meet these challenges, this article presents several techniques that together build a new approach for combining AL and semi-supervised learning (SSL) for support vector machines (SVM) in classification tasks.
https://pubs.acs.org/doi/full/10.1021/ci025620t
In each iteration a comparatively small batch of compounds is screened for binding activity toward this target. We employed the so-called “active learning paradigm” from Machine Learning for selecting the successive batches. Our main selection strategy is based on the maximum margin hyperplanegenerated by “Support Vector Machines”.
https://users.soe.ucsc.edu/~manfred/pubs/J54.pdf
a Machine Learning problem. Then Support Vector Machines and various selection strategies are briefly described. Here, we also discuss links to the active learning paradigm and provide motivations for the particular selection strategies. Finally we demonstrate and discuss the performance on two real data sets. We conclude with a summary and ...
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