On the Renormalization Group Explanation of Universality

It is commonly claimed that the universality of critical phenomena is explained through particular applications of the renormalization group. This article has three aims: to clarify the structure of the explanation of universality, to discuss the physics of such RG explanations, and to examine the extent to which universality is thus explained. The derivation of critical exponents proceeds via a real-space or a field-theoretic approach to the RG. Building on work by Mainwood, this article argues that these approaches ought to be distinguished: while the field-theoretic approach explains universality, the real-space approach fails to provide an adequate explanation

On the Renormalisation Group Explanation of Universality

It is commonly claimed that the universality of critical phenomena is explained through particular applications of the renormalisation group. This paper has three aims: to clarify the structure of the explanation of universality; to discuss the physics of such renormalisation group explanations; and to examine the extent to which universality is thus explained. The derivation of critical exponents proceeds via a real-space or a field-theoretic approach to the renormalisation group. Building on Mainwood (2006), this paper argues that these approaches ought to be distinguished: while the field-theoretic approach explains universality, the real-space approach fails to provide an adequate explanation

On the Renormalisation Group Explanation of Universality

It is commonly claimed that the universality of critical phenomena is explained through particular applications of the renormalisation group. This paper has three aims: to clarify the structure of the explanation of universality; to discuss the physics of such renormalisation group explanations; and to examine the extent to which universality is thus explained. The derivation of critical exponents proceeds via a real-space or a field-theoretic approach to the renormalisation group. Building on Mainwood (2006), this paper argues that these approaches ought to be distinguished: while the field-theoretic approach explains universality, the real-space approach fails to provide an adequate explanation

On the Renormalisation Group Explanation of Universality

It is commonly claimed that the universality of critical phenomena is explained through particular applications of the renormalisation group. This paper has three aims: to clarify the structure of the explanation of universality; to discuss the physics of such renormalisation group explanations; and to examine the extent to which universality is thus explained. The derivation of critical exponents proceeds via a real-space or a field-theoretic approach to the renormalisation group. Building on Mainwood (2006), this paper argues that these approaches ought to be distinguished: while the field-theoretic approach explains universality, the real-space approach fails to provide an adequate explanation

Sparse Transfer Learning for Interactive Video Search Reranking

Visual reranking is effective to improve the performance of the text-based video search. However, existing reranking algorithms can only achieve limited improvement because of the well-known semantic gap between low level visual features and high level semantic concepts. In this paper, we adopt interactive video search reranking to bridge the semantic gap by introducing user's labeling effort. We propose a novel dimension reduction tool, termed sparse transfer learning (STL), to effectively and efficiently encode user's labeling information. STL is particularly designed for interactive video search reranking. Technically, it a) considers the pair-wise discriminative information to maximally separate labeled query relevant samples from labeled query irrelevant ones, b) achieves a sparse representation for the subspace to encodes user's intention by applying the elastic net penalty, and c) propagates user's labeling information from labeled samples to unlabeled samples by using the data distribution knowledge. We conducted extensive experiments on the TRECVID 2005, 2006 and 2007 benchmark datasets and compared STL with popular dimension reduction algorithms. We report superior performance by using the proposed STL based interactive video search reranking.Comment: 17 page