NIPS
2000
13 years 6 months ago
2000
In theory, the Winnow multiplicative update has certain advantages over the Perceptron additive update when there are many irrelevant attributes. Recently, there has been much eff...
NIPS
2000
13 years 6 months ago
2000
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
NIPS
1998
13 years 6 months ago
1998
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
ICONIP
1998
13 years 6 months ago
1998
In this paper, we study the use of support vector machine in text categorization. Unlike other machine learning techniques, it allows easy incorporation of new documents into an e...
NIPS
2003
13 years 6 months ago
2003
This paper presents a method for learning a distance metric from relative comparison such as “A is closer to B than A is to C”. Taking a Support Vector Machine (SVM) approach,...
TREC
2004
13 years 6 months ago
2004
This paper reports our knowledge-ignorant machine learning approach to the triage task in TREC2004 genomics track, which is actually a text categorization problem. We applied Supp...
NIPS
2001
13 years 6 months ago
2001
This article presents a Support Vector Machine (SVM) like learning system to handle multi-label problems. Such problems are usually decomposed into many two-class problems but the...
NIPS
2004
13 years 6 months ago
2004
An analog system-on-chip for kernel-based pattern classification and sequence estimation is presented. State transition probabilities conditioned on input data are generated by an...
DMIN
2006
13 years 6 months ago
2006
: For the characteristics of malfunction diagnose system a model to classify fault printing based on support vector machines is discussed. The printing malfunctions have many class...
AAAI
2006
13 years 6 months ago
2006
One of the well known risks of large margin training methods, such as boosting and support vector machines (SVMs), is their sensitivity to outliers. These risks are normally mitig...