Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Data Mining - Concepts and Techniques.

Data Mining Practical Machine Learning Tools and Techniques

How to Do Things With Words

A Survey on Social Networks: Issues and Attacks

Tuberculosis (TB) has been one of the top ten causes of death in the world. As per the World Health Organization (WHO) around 1.8 million people have died due to tuberculosis in 2015. This paper aims to investigate the spatial and temporal variations in TB incident in South Asia (India, Bangladesh, Pakistan, Maldives, Nepal, and Sri-Lanka). Asia had been counted for the largest number of new TB cases in 2015. The paper underlines and relates the relationship between various features like gender, age, location, occurrence, and mortality due to TB in these countries for the period 1993-2012.

/pdf/analysing-tuberculosis-trends-in-south-asia-3l4j4gh39o.pdf

Analysing Tuberculosis Trends in South Asia

User experience is the ultimate quality of service criterion for modern WLAN networks. However, network configuration approaches are mainly network-centric. We envision a paradigm shift, empowering users in network management. We study how automated negotiation and collective intelligence can support the democratic configuration of a wireless network, leveraging client and provider interests. This new paradigm allows for flexible network configuration, which enables better exploitation of resources considering the clients’ real usage and needs, and a fair distribution of throughput among users.

Democratic Wireless Channel Assignment: Fair Resource Allocation in Wi-Fi Networks

Data analysts often prefer access to data in the form of original tuples (i.e., microdata), instead of pre-aggregated statistics, since the former offers advantages in information flexibility and availability. Two problems should be addressed before releasing microdata. First, individual’s privacy needs to be adequately protected. In general, the data will be anonymized before sharing. Second, the utility of the anonymized microdata should be maintained and common aggregate queries should be answered with reasonable accuracy. 
Most existing works on microdata anonymization are based on attribute generalization. Though popular, these approaches have limitations: the generalization of attributes make it difficult to answer typical aggregate queries with reasonable accuracy. 
This dissertation investigates new techniques to address the limitations of existing approaches. We propose to anonymize microdata through permutation-based approaches. In particular, we first extend existing privacy goals to better fit the protection requirement of numerical data, and develop a scheme to achieve this privacy goal through sensitive attribute permutation. Second, we propose a stronger privacy goal where an attacker can only learn from the microdata that an individual’s sensitive attribute follows a pre-specified target distribution, but nothing more. We combine sensitive attribute permutation and generalization techniques to achieve this goal. To get better query answers when the target distribution is far from that of the original microdata, we further provide mechanisms to allow users to better control the tradeoff between privacy and accuracy. Third, we extend our techniques to anonymize graph data and support the accurate answering of queries that involve graph properties. Specifically, we partition the nodes and relabel (a form of permutation) the nodes within the same partition. Finally, we study anonymization techniques that can support personalized privacy, which allows individuals to flexibly control the privacy protection they desire.

Munindar P. Singh

Papers

A Survey on Social Networks: Issues and Attacks

Analysing Tuberculosis Trends in South Asia

Democratic Wireless Channel Assignment: Fair Resource Allocation in Wi-Fi Networks

Microdata privacy protection through permutation-based approaches

Web Ontology Language