INTRODUCTION Insulin resistance (IR), a risk factor for the development of cardiovascular disease, is common among patients with rheumatoid arthritis (RA). Inflammation, and especially tumour necrosis factor alpha (TNFα), has been associated with IR, and the administration of anti-TNFα agents is suggested to improve insulin sensitivity. However obesity, a potent contributor to IR, may limit the...

Multiple instance learning (MIL) is a branch of machine learning that attempts to learn information from bags of instances. Many real-world applications such as localized content-based image retrieval and text categorization can be viewed as MIL problems. In this paper, we propose a new graph-based semi-supervised learning approach for multiple instance learning. By defining an instance-level g...

We consider the problem of verifying the identity of a distribution: Given the description of a distribution over a discrete support p = (p1, p2, . . . , pn), how many samples (independent draws) must one obtain from an unknown distribution, q, to distinguish, with high probability, the case that p = q from the case that the total variation distance (L1 distance) ||p− q||1 ≥ ε? We resolve this ...

The goal of traditional multi-instance learning (MIL) is to predict the labels of the bags, whereas in many real applications, it is desirable to get the instance labels, especially the labels of key instances that trigger the bag labels, in addition to getting bag labels. Such a problem has been largely unexplored before. In this paper, we formulate the Key Instance Detection (KID) problem, an...

Multi-instance (MI) learning is a variant of supervised machine learning, where each learning example contains a bag of instances instead of just a single feature vector. MI learning has applications in areas such as drug activity prediction, fruit disease management and image classification. This thesis investigates the case where each instance has a weight value determining the level of influ...

Multiple-Instance Learning (MIL) has attracted much attention of the machine learning community in recent years and many real-world applications have been successfully formulated as MIL problems. Over the past few years, several Instance Selection-based MIL (ISMIL) algorithms have been presented by using the concept of the embedding space. Although they delivered very promising performance, the...

Wei Li1 [email protected] Changhu Wang2 [email protected] Lei Zhang3 [email protected] Yong Rui2 [email protected] Bo Zhang1 [email protected] 1 State Key Lab of Intelligent Technology and Systems, TNList, Department of Computer Science and Technology, Tsinghua University Beijing 100084, China 2 Microsoft Research No. 5 Danling Street, Haidian District, Beijing 100080, China...

The UNC5 receptor family are chemorepulsive neuronal guidance receptors with additional functions outside the central nervous system. Previous studies have implicated that the UNC5B receptor influences the migration of leukocytes into sites of tissue inflammation. Given that this process is a critical step during the pathophysiology of myocardial ischemia followed by reperfusion (IR) we investi...

In recent years the study of the complexity of computational problems involving real numbers has been an increasing research area. A founda-tional paper has been 4] where a computational model |the real Turing machine| for dealing with the above problems was developed. One research direction that has been studied intensively during the last two years is the computational power of real Turing ma...