Structured ranking learning using cumulative distribution networks

Supplementary Information for “ Structured Ranking Learning using Cumulative Distribution Networks ”

Cumulative distribution networks and the derivative-sum-product algorithm

Abstract We introduce a new type of graphical model called a ‘cumulative distribution network’ (CDN), which expresses a joint cumulative distribution as a product of local functions. Each local function can be viewed as providing evidence about possible orderings, or rankings, of variables. Interestingly, we find that the conditional independence properties of CDNs are quite different from othe...

Exact inference and learning for cumulative distribution functions on loopy graphs

Abstract Many problem domains including climatology and epidemiology require models that can capture both heavy-tailed statistics and local dependencies. Specifying such distributions using graphical models for probability density functions (PDFs) generally lead to intractable inference and learning. Cumulative distribution networks (CDNs) provide a means to tractably specify multivariate heavy...

Perceptron-like Algorithms and Generalization Bounds for Learning to Rank

Learning to rank is a supervised learning problem where the output space is the space of rankings but the supervision space is the space of relevance scores. We make theoretical contributions to the learning to rank problem both in the online and batch settings. First, we propose a perceptron-like algorithm for learning a ranking function in an online setting. Our algorithm is an extension of t...

Cumulative distribution networks: Inference, estimation and applications of graphical models for cumulative distribution functions

Cumulative distribution networks: Inference, estimation and applications of graphical models for cumulative distribution functions Jim C. Huang Doctor of Philosophy Graduate Department of Electrical and Computer Engineering University of Toronto 2009 This thesis presents a class of graphical models for directly representing the joint cumulative distribution function (CDF) of many random variabl...