Nonlinear Information Bottleneck

Information bottleneck (IB) is a technique for extracting information in one random variable $X$ that is relevant for predicting another random variable $Y$. IB works by encoding $X$ in a compressed "bottleneck" random variable $M$ from which $Y$ can be accurately decoded. However, finding the optimal bottleneck variable involves a difficult optimization problem, which until recently has been considered for only two limited cases: discrete $X$ and $Y$ with small state spaces, and continuous $X$ and $Y$ with a Gaussian joint distribution (in which case optimal encoding and decoding maps are linear). We propose a method for performing IB on arbitrarily-distributed discrete and/or continuous $X$ and $Y$, while allowing for nonlinear encoding and decoding maps. Our approach relies on a novel non-parametric upper bound for mutual information. We describe how to implement our method using neural networks. We then show that it achieves better performance than the recently-proposed "variational IB" method on several real-world datasets

Softer perspectives on enhancing the patient experience using IS/IT

Purpose – This paper aims to argue that the implementation of the Choose and Book system has failed due to the inability of project sponsors to appreciate the complex and far-reaching softer implications of the implementation, especially in a complex organisation such as the NHS, which has multifarious stakeholders. Design/methodology/approach – The authors use practice-oriented research to try and isolate key parameters. These parameters are compared with existing conventional thinking in a number of focused areas. Findings – Like many previous NHS initiatives, the focus of this system is in its obvious link to patients. However we find that although this project has cultural, social and organisational implications, programme managers and champions of the Connecting for Health programme emphasised the technical domains to IS/IT adoption. Research limitations/implications – This paper has been written in advance of a fully implemented Choose and Book system. Practical implications – The paper requests that more attention be paid to the softer side of IS/IT delivery, implementation, introduction and adoption. Originality/value – The paper shows that patient experience within the UK healthcare sector is still well below what is desired

The benefits of coding over routing in a randomized setting

A novel randomized network coding approach for robust, distributed transmission and compression of information in networks is presented, and its advantages over routing-based approaches is demonstrated

Antigenic and biochemical characterization of bovine rotavirus V1005, a new member of rotavirus serotype 10

Bovine rotavirus (BRV) V1005 is serologically distinct from rotavirus serotypes 1, 2, 3, 4, 5, 6, 8 and 9. BRV V1005 showed cross-reactions with BRV B223, the American prototype of serotype 10 rotavirus, and with BRV E4049, a British serotype 10 isolate. BRV V1005 was, however, not neutralized by four monoclonal antibodies directed against VP7 of BRV B223. Two-way cross-reactions were observed between BRV V1005 and a reassortant rotavirus containing the VP4 from BRV UK. In addition the major tryptic cleavage product of VP4, VP5*, from BRV V1005 is indistinguishable by peptide mapping and its isoelectric point from the homologous protein of BRV UK, but is clearly different from VP5* of BRV NCDV. The peptide map of VP7 from BRV V1005 differed from that obtained for VP7 of BRV U

Employers Should Owe a Duty of Loyalty to Their Workers

An employee’s overarching legal commitment to his or her employer is commonly known as the “duty of loyalty.” This lopsided duty of loyalty exacerbates the inordinate power that employers possess over their workers. We propose that the duty of loyalty owed by workers to their employers be made reciprocal: employers should also owe a general duty of loyalty and care towards their employees

Byzantine modification detection in multicast networks using randomized network coding

Distributed randomized network coding, a robust approach to multicasting in distributed network settings, can be extended to provide Byzantine modification detection without the use of cryptographic functions is presented in this paper

Byzantine Modification Detection in Multicast Networks With Random Network Coding

An information-theoretic approach for detecting Byzantine or adversarial modifications in networks employing random linear network coding is described. Each exogenous source packet is augmented with a flexible number of hash symbols that are obtained as a polynomial function of the data symbols. This approach depends only on the adversary not knowing the random coding coefficients of all other packets received by the sink nodes when designing its adversarial packets. We show how the detection probability varies with the overhead (ratio of hash to data symbols), coding field size, and the amount of information unknown to the adversary about the random code