NDLI: DCMSVM: Distributed parallel training for single-machine multiclass classifiers

Content Provider	IEEE Xplore Digital Library
Author	Han, X. Berg, A.C.
Copyright Year	2012
Description	Author affiliation: Computer Science Department, Stony Brook University (Han, X.; Berg, A.C.)
Abstract	We present an algorithm and implementation for distributed parallel training of single-machine multiclass SVMs. While there is ongoing and healthy debate about the best strategy for multiclass classification, there are some features of the single-machine approach that are not available when training alternatives such as one-vs-all, and that are quite complex for tree based methods. One obstacle to exploring single-machine approaches on large datasets is that they are usually limited to running on a single machine! We build on a framework borrowed from parallel convex optimization — the alternating direction method of multipliers (ADMM) — to develop a new consensus based algorithm for distributed training of single-machine approaches. This is demonstrated with an implementation of our novel sequential dual algorithm (DCMSVM) which allows distributed parallel training with small communication requirements. Benchmark results show significant reduction in wall clock time compared to current state of the art multiclass SVM implementation (Liblinear) on a single node. Experiments are performed on large scale image classification including results with modern high-dimensional features.
Starting Page	3554
Ending Page	3561
File Size	333567
Page Count	8
File Format	PDF
ISBN	9781467312264
ISSN	10636919
e-ISBN	9781467312288
e-ISBN	9781467312271
DOI	10.1109/CVPR.2012.6248099
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Accuracy Optimization Support vector machines Convergence Equations Computational modeling
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Large-Scale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex

Incremental Training of Multiclass Support Vector Machines

Dcmsvm: distributed parallel training for single-machine multiclass classifiers.

Multitask multiclass privileged information support vector machines

DCMSVM: Distributed Parallel Training For Single-Machine Multiclass Classifiers

Fusing subcategory probabilities for texture classification

Linear dependency modeling for feature fusion

Active scene recognition with vision and language

Max-margin additive classifiers for detection

DCMSVM: Distributed parallel training for single-machine multiclass classifiers

Similar Documents

Large-Scale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex

Incremental Training of Multiclass Support Vector Machines

Dcmsvm: distributed parallel training for single-machine multiclass classifiers.

Multitask multiclass privileged information support vector machines

DCMSVM: Distributed Parallel Training For Single-Machine Multiclass Classifiers

Fusing subcategory probabilities for texture classification

Linear dependency modeling for feature fusion

Active scene recognition with vision and language

Max-margin additive classifiers for detection

DCMSVM: Distributed parallel training for single-machine multiclass classifiers