• Voting rules from random relations 

  Wilson, Nic (IOS Press, 2020-08)

  We consider a way of generating voting rules based on a random relation, the winners being alternatives that have the highest probability of being supported. We define different notions of support, such as whether an ...
• Generating voting rules from random relations 

  Wilson, Nic (International Foundation for Autonomous Agents and MultiAgent Systems (IFAAMAS)., 2019-05)

  We consider a way of generating voting rules based on a random relation, the winners being alternatives that have the highest probability of being supported. We consider different notions of support, such as whether an ...
• Efficient inference and computation of optimal alternatives for preference languages based on lexicographic models 

  Wilson, Nic; George, Anne-Marie (International Joint Conferences on Artificial Intelligence, 2017-08)

  We analyse preference inference, through consistency, for general preference languages based on lexicographic models. We identify a property, which we call strong compositionality , that applies for many natural kinds of ...
• Rescale-invariant SVM for binary classification 

  Montazery, Mojtaba; Wilson, Nic (International Joint Conferences on Artificial Intelligence, 2017-08)

  Support Vector Machines (SVM) are among the best-known machine learning methods, with broad use in different scientific areas. However, one necessary pre-processing phase for SVM is normalization (scaling) of features, ...
• Dominance and optimisation based on scale-invariant maximum margin preference learning 

  Montazery, Mojtaba; Wilson, Nic (International Joint Conferences on Artificial Intelligence, 2017-08)

  In the task of preference learning, there can be natural invariance properties that one might often expect a method to satisfy. These include (i) invariance to scaling of a pair of alternatives, e.g., replacing a pair ( ...

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