Events

Mohammed Alliheedi, PhD candidate
David R. Cheriton School of Computer Science

Ontologies must provide the entities, concepts, and relations required by the domain being represented. The domain of interest in this paper is the biochemistry experimental procedure. The ontology language being used is OWL-DL. OWL-DL was adopted due to its well-balanced flexibility among expressiveness (e.g., class description, cardinality restriction, etc.), completeness, and decidability. These procedures are composed of procedure steps, which can be represented as sequences. Sequences are composed of totally ordered, partially ordered, and alternative subsequences. 

Chris Eliasmith, Director of the Centre for Theoretical Neuroscience
Department of Systems Design Engineering

Spiking neural networks (SNNs) have received little attention from the AI community, although they compute in a fundamentally different — and more biologically inspired — manner than standard artificial neural networks (ANNs). This can be partially explained by the lack of hardware that natively supports SNNs. However, several groups have recently released neuromorphic hardware that supports SNNs. 

Edith Elkind, Department of Computer Science
University of Oxford

Suppose that a group of agents want to select k > 1 alternatives from a given set, and each agent indicates which of the alternatives are acceptable to her: the alternatives could be conference submissions, applicants for a scholarship or locations for a fast food chain. In this setting it is natural to require that the set of winners represents the voters fairly, in the sense that large groups of voters with similar preferences have at least some of their approved alternatives in the winning set. 

Ivan Stelmakh, PhD candidate
Machine Learning Department, School of Computer Science
Carnegie Mellon University

Peer review is the backbone of scholarly research and fairness of this process is crucial for the successful development of academia. In this talk, we will discuss our two recent works on fairness of peer review. In the first part of the talk, we will focus on the automated assignment of papers to reviewers in the conference setup. We will show that the assignment procedure currently employed by NeurIPS and ICML does not guarantee fairness and may discriminate against some submissions. In contrast, we will present the assignment algorithm that simultaneously ensures fairness and accuracy of the resulting allocation. 

Kristian Kersting
Computer Science Department
Centre for Cognitive Science
Technische Universität Darmstadt

Our minds make inferences that appear to go far beyond standard machine learning. Whereas people can learn richer representations and use them for a wider range of learning tasks, machine learning algorithms have been mainly employed in a stand-alone context, constructing a single function from a table of training examples. 

Qiang Liu, Department of Computer Science
University of Texas at Austin

As a fundamental technique for approximating and bounding distances between probability measures, Stein’s method has caught the attention in the machine learning community recently; some of the key ideas in Stein’s method have been leveraged and extended for developing practical and efficient computational methods for learning and using large scale, intractable probabilistic models.