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http://alex.smola.org/drafts/KDD12.pdf
single machine. Outline. We begin by giving an overview of dual descent algorithms for linear Support Vector Machines in section 2. Subsequently Section 3 gives a detailed description of the nested loop used in traversing through data in core memory and streaming from disk. Experimental results are …
https://dl.acm.org/citation.cfm?id=2339559
This paper proposes StreamSVM, the first algorithm for training linear Support Vector Machines (SVMs) which takes advantage of these properties by integrating caching with optimization. StreamSVM works by performing updates in the dual, thus obviating …Cited by: 15
https://www.researchgate.net/publication/252065202_Linear_Support_Vector_Machines_via_Dual_Cached_Loops
Linear Support Vector Machines (SVM) is one of the most popular tools to deal with such large-scale sparse data. This paper presents a novel dual coordinate descent method for linear SVM with L1 ...
https://www.soe.ucsc.edu/events/event/2777
Optimizing Linear Support Vector Machines via Dual Cache Loops ... StreamSVM is a solver for Linear SVMs that exploits the different speeds of computing on the CPU and accessing data from disk. StreamSVM works by performing coordinate updates on the dual, thus avoiding the need to rebalance frequently visited examples. Further, we trade-off ...
https://static.aminer.org/pdf/PDF/003/445/671/Linear-Support-Vector-Machines-Via-Dual-Cached-Loops.pdf
Linear Support Vector Machines via Dual Cached Loops Shin Matsushima Information Science and Technology The University of Tokyo, Tokyo [email protected]
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.591.4400
dual cached loop shin matsushima linear support vector machine data ex-pansion accurate solution several diverse thread linear svm solver elaborate hierarchy storage subsystem different speed modern computer hardware first svm optimization algorithm
http://suyongeum.com/ML/tutorials/tutorial3-yang.pdf
Linear model Support vector machine: Margin: the smallest distance between the decision boundary and any of the samples maximizing the margin ⇒ a particular decision boundary Location of boundary is determined by support vectors 3 Linear separableH Class A Class B 𝑇 + =0 H1 H2 1 1 2 2 𝑇 + =1 𝑇 + =−1 Support …
https://svm.csie.ntu.edu.tw/~svm/wiki/seminar
8/22 Wei-Lun presented Linear Support Vector Machines via Dual Cached Loops. 8/23 Wei-Lun continued to present Linear Support Vector Machines via Dual Cached Loops. 8/24 Yu-Chin presented A Dual Coordinate Descent Method for Large-scale Linear SVM.
https://cs.adelaide.edu.au/~chhshen/teaching/ML_SVR.pdf
•Support Vector Machines •Boosting •Linear Regression •Support Vector Regression Group data based on their ... Dual problem for non-linear case •Primal •Dual ... –Cache memory in kilobytes (CACH) –Minimum channels in units (CHMIN)
https://jeremykun.com/2017/06/05/formulating-the-support-vector-machine-optimization-problem/
Jun 05, 2017 · However, they often suffer from numerical stability issues and have less-than-satisfactory runtime. Luckily, the form in which we’ve expressed the support vector machine problem is specific enough that we can analyze it directly, and find a way to solve it without appealing to general-purpose numerical solvers.
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