Research Publications

Placeholder
 
Search | Show all
All
Narrow your search
« 1 2 3 4 5 ... 29 30 »

Results per Page 10 25 50 100 250
293 result(s)
By Type
By Year
By Research Group
Ehsan Abbasnejad, Scott Sanner, PAscal Poupart
Bayesian approaches to preference learning using Gaussian Processes (GPs) are attractive due to their ability to explicitly model uncertainty in users' latent utility functions; unfortunately existing techniques have cubic time complexity in the number of...
IJCAI - August 2013
Zahra Zamani, Scott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros
Recent advances in solutions to Hybrid MDPs with discrete and continuous state and action spaces have significantly extended the class of MDPs for which exact solutions can be derived, albeit at the expense of a restricted transition noise model. In ...
International Joint Conference on Artificial Intelligence (IJCAI) - August 2013
Twitter: the world of 140 characters poses serious challenges to the efficacy of topic models on short, messy text. While topic models such as Latent Dirichlet Allocation (LDA) have a long history of successful application to news articles and ...
The 36th Annual ACM SIGIR Conference - July 2013
Luis Vianna Rocha, Scott Sanner, Leliane Nunes de Barros
Recent advances in symbolic dynamic programming (SDP) combined with the extended algebraic decision diagram (XADD) data structure have provided exact solutions for mixed discrete and continuous (hybrid) MDPs with piecewise linear dynamics and ...
Uncertainty in Artificial Intelligence - July 2013
Tan Nguyen, Scott Sanner
While convex losses for binary classification are attractive due to the existence of numerous (provably) efficient methods for finding their global optima, they are sensitive to outliers. On the other hand, while the non-convex 0--1 loss is robust to ...
International Conference on Machine Learning (ICML) - June 2013
Lan Du, Wray Buntine, Mark Johnson
We present a new hierarchical Bayesian model for unsupervised topic segmentation.~This new model integrates a point-wise boundary sampling algorithm used in Bayesian segmentation into a structured topic model that can capture a simple hierarchical ...
2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - June 2013
Lachlan McCalman, Simon O'Callaghan, Fabio Ramos
We present a novel estimation algorithm for filtering and regression with a number of advantages over existing methods. The algorithm has wide application in robotics as no assumptions are made about the underlying distributions, it can represent ...
IEEE International Conference on Robots and Automation (ICRA) - May 2013
Van Trung Nguyen, Edwin Bonilla
In multi-output regression applications the correlations between the response variables may vary with the input space and can be highly non-linear. Gaussian process regression networks (GPRNs) are flexible and effective models to represent such complex ...
International Conference on Artificial Intelligence and Statistics (AISTATS) - April 2013
Lawrence Cavedon, David Martinez, Hanna Suominen, Michelle Ananda-Rajah, Graham Pitson, Karin Verspoor
Much clinical data available in electronic health records (EHRs) are in text format. Developing text processing and mining techniques for such data is necessary for realizing the full value of this data, to support data-driven analysis, decision-making, ...
Big Data in Health and Biomedicine - April 2013
Weihong Wang, Zhidong Li, Yang Wang, Fang Chen
Pupillary response is a popular physiological index of cognitive workload that can be used for design and evaluation of adaptive interface in various areas of human-computer interaction (HCI) research. However, in practice various confounding factors ...
International Conference on Intelligent User Interface (IUI) 2013 - March 2013