A photograph of the Department of Chemical Engineering taken in January 2008

The Department of Chemical Engineering in the snow, February 2007

Photograph of the arch leading to the New Museums Site

This paper introduces a novel measure-theoretic theory for machine learning that does not require statistical assumptions. Based on this theory, a new regularization method in deep learning is derived and shown to ...

We previously developed Konure, a tool that uses active learning to infer the functionality of database applications. An alternative approach is to observe the inputs, outputs, and database traffic from a running ...

The principle of Continuous Double Auctioning (CDA) is known to provide an efficient way of matching supply and demand among distributed selfish participants with limited information. However, the literature indicates that ...

Electronic medical record (EMR) systems are increasingly being adopted in low- and middle-income countries. This provides an opportunity to support task-shifted health workers with guideline-based clinical decision support ...

We present a new technique that uses active learning to infer models of applications that manipulate relational databases. This technique comprises a domain-specific language for modeling applications that access ...

In a model of physics taking place on a discrete set of points that approximates Minkowski space, one might perhaps expect there to be an empirically identifiable preferred frame. However, the work of Dowker et al (2004 ...

An Introduction to Ontology Engineering is a free online textbook that provides an overview of ontology engineering, including logics and automated reasoning, methods and methodologies, top-down ontology development with ...

This archive contains the code and data for the workshop article "A New Approach to Animacy Detection," published in 2018 in the the 27th International Conference on Computational Linguistics (COLING 2018), in Santa Fe, ...

This thesis considers the case of mobile crime-reporting systems that have emerged as an effective and efficient data collection method in low and middle-income countries. Analyzing the data, can be helpful in addressing ...

With the rise of autonomous systems, there is a need for them to have high levels of robustness and safety. This robustness can be achieved through systems that are self-repairing. Underlying this is the ability to diagnose ...

Learning models of decision-making behavior during sequential tasks is useful across a variety of applications, including human-machine interaction. In this paper, we present an approach to learning such models within ...

This paper presents an analytic solution for the sound generated by an unsteady gust interacting with a semi-infinite flat plate with a piecewise linear periodic leading edge. The Wiener-Hopf method is used in conjunction ...

With a direct analysis of neural networks, this paper presents a mathematically tight generalization theory to partially address an open problem regarding the generalization of deep learning. Unlike previous bound-based ...

The Met Office has investigated the use of natural language generation (NLG) technologies to streamline the production of weather forecasts. Their approach would be of great benefit in South Africa because there is no fast ...

Community Health Workers (CHWs) are an integral part of the rural health system, and it is imperative that their voices are accommodated in digital health projects. In the mobile health education project discussed in this ...

The design of effective, robust and autonomous controllers for multi-agent and multi-robot systems is a long-standing problem in the fields of computational intelligence and robotics. Whilst nature-inspired problem-solving ...