Journal ArticleDOI
LIBSVM: A library for support vector machines
Chih-Chung Chang,Chih-Jen Lin +1 more
TLDR
Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.Abstract:
LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popularity in machine learning and many other areas. In this article, we present all implementation details of LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.read more
Citations
More filters
Journal ArticleDOI
Day-ahead load forecast using random forest and expert input selection
TL;DR: This paper proposes a short term load predictor, able to forecast the next 24 h of load, constructed following an online learning process using random forest and refined by expert feature selection using a set of if–then rules.
Journal ArticleDOI
Activity Discovery and Activity Recognition: A New Partnership
TL;DR: This paper describes a method by which activity discovery can be used to identify behavioral patterns in observational data and demonstrates that activity discovery not only sheds light on behavioral patterns, but it can also boost the performance of recognition algorithms.
Journal ArticleDOI
Recommendation as link prediction in bipartite graphs
Xin Li,Hsinchun Chen +1 more
TL;DR: This work proposes a kernel-based recommendation approach and design a novel graph kernel that inspects customers and items related to the focal user-item pair as its context to predict whether there may be a link and proves the validity and computational efficiency of the graph kernel.
Journal ArticleDOI
Taking the bite out of automated naming of characters in TV video
TL;DR: It is demonstrated that high precision can be achieved by combining multiple sources of information, both visual and textual, by automatic generation of time stamped character annotation by aligning subtitles and transcripts.
Proceedings ArticleDOI
Gender Bias in Contextualized Word Embeddings
TL;DR: In this article, the authors quantify, analyze and mitigate gender bias exhibited in ELMo's contextualized word vectors, and explore two methods to mitigate such gender bias and show that the bias demonstrated on WinoBias can be eliminated.
References
More filters
Journal ArticleDOI
Support-Vector Networks
Corinna Cortes,Vladimir Vapnik +1 more
TL;DR: High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.
Statistical learning theory
TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
Proceedings ArticleDOI
A training algorithm for optimal margin classifiers
TL;DR: A training algorithm that maximizes the margin between the training patterns and the decision boundary is presented, applicable to a wide variety of the classification functions, including Perceptrons, polynomials, and Radial Basis Functions.
A Practical Guide to Support Vector Classication
TL;DR: A simple procedure is proposed, which usually gives reasonable results and is suitable for beginners who are not familiar with SVM.
Journal ArticleDOI
A comparison of methods for multiclass support vector machines
Hsu Chih-Wei,Chih-Jen Lin +1 more
TL;DR: Decomposition implementations for two "all-together" multiclass SVM methods are given and it is shown that for large problems methods by considering all data at once in general need fewer support vectors.