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Large margin classification using the perceptron algorithm

Yoav Freund, Robert E. Schapire
1998 Proceedings of the eleventh annual conference on Computational learning theory - COLT' 98  
Like Vapnik's maximal-margin classifier, our algorithm takes advantage of data that are linearly separable with large margins.  ...  We introduce and analyze a new algorithm for linear classification which combines Rosenblatt's perceptron algorithm with Helmbold and Warmuth's leave-one-out method.  ...  However, as we shall see, when perceptrons are used together with kernels, the excess in memory and computation is really quite minimal. 2.  ... 
doi:10.1145/279943.279985 dblp:conf/colt/FreundS98 fatcat:kwakvsczu5flxkun2pbaqqmggy


Hemant Panwar
2020 Zenodo  
The proposed classification algorithm implements margin in classical perceptron algorithm, to reduce generalized errors by maximizing margin of separating hyperplane.  ...  Algorithm uses the same updation rule with the perceptron, to converge in a finite number of updates to solutions, possessing any desirable fraction of the margin.  ...  Such algorithms include Relaxed Online Maximum Margin Algorithm (ROMMA) [4] , Approximate Large Margin Algorithm (ALMA) [5] . , k x [6] .  ... 
doi:10.5281/zenodo.4271590 fatcat:btc7kqlvxnabplzfcmj4pes6z4


Bernd Jürgen Falkowski
2006 Information Technology and Control  
In order to achieve better generalization properties the additional use of an iterative large margin perceptron algorithm is investigated.  ...  The importance of classification algorithms in the context of risk assessment is briefly explained.  ...  Hence in this paper the additional use of an iterative large margin perceptron algorithm as proposed by Krauth and Mezard, cf. [13] is treated.  ... 
doi:10.5755/j01.itc.35.3.11764 fatcat:aeepzkootfcfvgdwepy53dp6s4

Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain [chapter]

Eneldo Loza Mencía, Johannes Fürnkranz
2010 Lecture Notes in Computer Science  
Both use the simple but very efficient perceptron algorithm as underlying classifier.  ...  In this paper we evaluate the performance of multilabel classification algorithms on two classification tasks related to documents of the EUR-Lex database of legal documents of the European Union.  ...  Acknowledgements This work was supported by the EC 6th framework project ALIS (Automated Legal Information System).  ... 
doi:10.1007/978-3-642-12837-0_11 fatcat:rv6eacprzrfklgrin7f4k7egjq

Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice [chapter]

Hsuan-Tien Lin, Ling Li
2006 Lecture Notes in Computer Science  
Both our approaches not only are simpler than existing algorithms, but also have a stronger connection to the large-margin bounds.  ...  We derive novel largemargin bounds of common error functions, such as the classification error and the absolute error.  ...  Conclusion We proposed a thresholded ensemble model for ordinal regression, and defined margins for the model. Novel large-margin bounds of common error functions were proved.  ... 
doi:10.1007/11894841_26 fatcat:zw6h27h7sraepmb2a5jgh77phq

Ranking and Reranking with Perceptron

Libin Shen, Aravind K. Joshi
2005 Machine Learning  
We apply the new perceptron algorithms to the parse reranking and machine translation reranking tasks, and study the performance of reranking by employing various definitions of the margins.  ...  Compared to the approach of using pairwise objects as training samples, the new algorithms reduces the data complexity and training time.  ...  Acknowledgements We thank anonymous reviewers for useful comments.  ... 
doi:10.1007/s10994-005-0918-9 fatcat:5uouaaawafcqvlsgrfybppb4tu

Links between perceptrons, MLPs and SVMs

Ronan Collobert, Samy Bengio
2004 Twenty-first international conference on Machine learning - ICML '04  
We propose to study links between three important classification algorithms: Perceptrons, Multi-Layer Perceptrons (MLPs) and Support Vector Machines (SVMs).  ...  We first study ways to control the capacity of Perceptrons (mainly regularization parameters and early stopping), using the margin idea introduced with SVMs.  ...  Acknowledgments This research has been carried out in the framework of the Swiss NCCR project (IM)2, and in the framework of the PASCAL European Network of Excellence, funded by the Swiss OFES.  ... 
doi:10.1145/1015330.1015415 dblp:conf/icml/CollobertB04 fatcat:akqtpkj2hbhq7f4gu7po35e5su

Flexible Margin Selection for Reranking with Full Pairwise Samples [chapter]

Libin Shen, Aravind K. Joshi
2005 Lecture Notes in Computer Science  
Perceptron like large margin algorithms are introduced for the experiments with various margin selections.  ...  Compared to the previous perceptron reranking algorithms, the new algorithms use full pairwise samples and allow us to search for margins in a larger space.  ...  Acknowledgments We thank Michael Collins for help concerning the data set.  ... 
doi:10.1007/978-3-540-30211-7_47 fatcat:dofawe5kpvgkxj2qan5gxl53s4

Perceptron like Algorithms for Online Learning to Rank [article]

Sougata Chaudhuri, Ambuj Tewari
2016 arXiv   pre-print
Perceptron is a classic online algorithm for learning a classification function.  ...  A modern perspective on perceptron for classification is that it is simply an instance of online gradient descent (OGD), during mistake rounds, using the hinge loss function.  ...  Acknowledgments We gratefully acknowledge the support of NSF under grant IIS-1319810. We also thank Prateek Jain for pointing out the relevant question on perceptron bound for NDCG cut-off at k m.  ... 
arXiv:1508.00842v4 fatcat:j6ntwore6zfndoohsvj2ampysy

Highly Scalable and Provably Accurate Classification in Poincare Balls [article]

Eli Chien, Chao Pan, Puoya Tabaghi, Olgica Milenkovic
2021 arXiv   pre-print
The gist of our approach is to focus on Poincar\'e ball models and formulate the classification problems using tangent space formalisms.  ...  Our results include a new hyperbolic and second-order perceptron algorithm as well as an efficient and highly accurate convex optimization setup for hyperbolic support vector machine classifiers.  ...  For large margin classification, we further required that the learnt w achieves the largest possible margin, max w∈TpB n min i∈[N ] y i h w,p (x i )d(x i , H w,p ). (10) A.  ... 
arXiv:2109.03781v3 fatcat:hpicmn6zyjfxblf5syfpofm5em

Classification and Ranking Approaches to Discriminative Language Modeling for ASR

Erinç Dikici, Murat Semerci, Murat Saraclar, Ethem Alpaydin
2013 IEEE Transactions on Audio, Speech, and Language Processing  
We formulate this both as a classification and a ranking problem and employ the perceptron, the margin infused relaxed algorithm (MIRA) and the support vector machine (SVM).  ...  Using the MIRA or SVM does not lead to any further improvement over the perceptron but the use of ranking as opposed to classification leads to a 0.4% reduction in word error rate (WER) which is statistically  ...  ACKNOWLEDGMENT The authors would like to thank Ebru Arısoy for the baseline DLM setup.  ... 
doi:10.1109/tasl.2012.2221461 fatcat:lsqerv2g3zhczcklfu5hcnce4u

Multi-class protein fold recognition using adaptive codes

Eugene Ie, Jason Weston, William Stafford Noble, Christina Leslie
2005 Proceedings of the 22nd international conference on Machine learning - ICML '05  
In order to compare against widely used methods in protein sequence analysis, we also test nearest neighbor approaches based on the PSI-BLAST algorithm.  ...  We develop a novel multi-class classification method based on output codes for the problem of classifying a sequence of amino acids into one of many known protein structural classes, called folds.  ...  Acknowledgments We would like to thank Thorsten Joachims for helpful suggestions on the implementation of SVM-Struct and Asa Ben-Hur for helpful comments on the manuscript.  ... 
doi:10.1145/1102351.1102393 dblp:conf/icml/IeWNL05 fatcat:x4pr34j2wvc5lce2dbjnhngdwe

Perceptron Learning of Modified Quadratic Discriminant Function

Tong-Hua Su, Cheng-Lin Liu, Xu-Yao Zhang
2011 2011 International Conference on Document Analysis and Recognition  
Recent advances justify the efficacy of minimum classification error criteria in learning MQDF (MCE-MQDF). We provide an alternative choice to MCE-MQDF based on the Perceptron learning (PL-MQDF).  ...  For better generalization performance, we propose a new dynamic margin regularization.  ...  Active Set Technique We employ active set technique to speed up the training process of Perceptron algorithm. If a instance invokes a classification error or margin error, we say it "active".  ... 
doi:10.1109/icdar.2011.204 dblp:conf/icdar/SuLZ11 fatcat:ppwq33rwgbfd5kepk3kt7dg5ya

A learning rule for very simple universal approximators consisting of a single layer of perceptrons

Peter Auer, Harald Burgsteiner, Wolfgang Maass
2008 Neural Networks  
We show that this assumption is not true, by exhibiting a simple learning algorithm for parallel perceptrons -the parallel delta rule ( p-delta rule).  ...  In spite of their simplicity, such circuits can compute any Boolean function if one views the majority of the binary perceptron outputs as the binary output of the parallel perceptron, and they are universal  ...  In our setting we use the clear margin to stabilize the output of the parallel perceptron.  ... 
doi:10.1016/j.neunet.2007.12.036 pmid:18249524 fatcat:75kvkyccgnfqhpyib6u3dk754e

Approximate maximum margin algorithms with rules controlled by the number of mistakes

Petroula Tsampouka, John Shawe-Taylor
2007 Proceedings of the 24th international conference on Machine learning - ICML '07  
classification with maximum margin.  ...  We present a family of Perceptron-like algorithms with margin in which both the "effective" learning rate, defined as the ratio of the learning rate to the length of the weight vector, and the misclassification  ...  Our purpose here is to address the maximal margin classification problem in the context of Perceptron-like algorithms which, however, differ from the above variants in that the "effective" learning rate  ... 
doi:10.1145/1273496.1273610 dblp:conf/icml/TsampoukaS07 fatcat:ikcabgm55rbddlnrkefyislvsi
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