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By Year By Research Group | 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... 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 ... 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 ... 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 ... 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 ... 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 ... 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 ... 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 ... 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, ... 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 ... A person’s cognitive state and capacity at a given moment deeply impact their decision making and perceived user experience, but are still very difficult to evaluate objectively, unobtrusively, and in real-time. Focusing on generating smart pen or stylus ... The introduction of plug-in electric vehicles (PEVs) represents an unprecedented interaction between the road network and electricity grid. By replacing the traditional fuel source, petrol, with electricity, PEVs will increase the demand for electric ... Verbal communication at nursing shift changes provides an accurate representation of patients’ background and current state of clinical management. However, over two thirds of this valuable handover information is lost after three to five shifts if ... We address the task of extracting information from free-text histopathology reports: such information includes cancer staging and tumour characteristics. In particular, we investigate the stability of a text mining model that was constructed from records ... Object detection is an important and challenging problem in the field of computer vision. Classical object detection approaches such as background subtraction and saliency detection do not require manual collection of training samples, but can be easily... The introduction of plug-in electric vehicles (PEVs) represents an unprecedented interaction between the road network and electricity grid. In this new integrated system, travel demand, behavior, and traffic congestion will influence the temporal and ... In order to exploit the potential of plug-in electric vehicles (PEVs) as a sustainable form of transport, this novel technology must be integrated into the traditional transport system planning process. This work takes a step in that direction by ... Measuring cognitive load changes can contribute to better treatment of patients, can help design effective strategies to reduce medical errors among clinicians and can facilitate user evaluation of health care information systems. This paper proposes an ... Statistical learning and sequential prediction are two different but related formalisms to study the quality of predictions. Mapping out their relations and transferring ideas is an active area of investigation. We provide another piece of the puzzle ... Geolocation prediction is vital to geospatial applications like localised search and local event detection. Predominately, social media geolocation models are based on full text data, including common words with no geospatial dimension (e.g.\... We present a novel top modelling-based methodology to track emerging events in microblogs such as Twitter. Our topic model has an in-built update mechanism based on time slices and implements a dynamic vocabulary. We first show that the method is... Online discussion forums are a valuable means for users to resolve specific information needs, both interactively for the participants and statically for users who search/browse over historical thread data. However, the complex structure of forum... Automatically extracting terminology and index terms from scientific literature is useful for a variety of digital library, indexing and search applications. This task is non-trivial, complicated by domain-specific terminology and a steady ... We present a new formulation for attacking binary classification problems. Instead of relying on convex losses and regularisers such as in SVMs, logistic regression and boosting, or instead non-convex but continuous formulations such as those encountered ... The ALTA shared task ran for the third time in 2012 with the aim of bringing research students together to work on the same task and data set to program and compare their methods for a current research problem. The task was based on the recent study ... Clinical shift handover is the transfer of professional responsibility for patient care to another person. While verbal handover provides a good picture of care, after 3-5 shifts 100% of this information is lost or transferred incorrectly if notes are not... Partially-observable Markov decision processes (POMDPs) provide a powerful model for real-world sequential decision-making problems. In recent years, point- based value iteration methods have proven to be extremely effective techniques for finding (... We strengthen recent connections between prediction markets and learning by showing that a natural class of market makers can be understood as performing stochastic mirror descent when trader demands are sequentially drawn from a fixed distribution. This ... High cognitive load arises from complex time- and safety-critical tasks (e.g., mapping out flight paths, monitoring traffic, or even managing nuclear reactors), which cause stress, errors and diminished performance. Over the past five years, our research ... Health data includes all health-related content in all data formats, document types, information systems, publication media and languages from all specialties, organizations, regions, states and countries. Examples include private data on electronic ... One of the potentially most relevant pieces of metadata for filtering studies in environmental science is the geographic region in which the study took place (the ``study region''). In this paper, we apply support vector machines to the automatic ... We present a method to estimate word use similarity independent of an external sense inventory. This method utilizes a topic-modelling approach to compute the similarity in usage of a single word across a pair of sentences, and we evaluate our ... Galvanic Skin Response (GSR) has recently attracted researchers’ attention as a prospective physiological indicator of cognitive load and emotions. However, it has commonly been investigated through single or few measures and in one experimental scenario.... A key problem in statistics and machine learning is the determination of network structure from data. We consider the case where the structure of the graph to be reconstructed is known to be scale-free. We show that in such cases it is natural to ... The process of finding the best locations for drilling in geothermal exploration requires the collection of vast amounts of information. Gravity, magnetism, seismicity, radiometric, magnetotellurics and drilling data are commonly used to infer specific ... Humans experience cognitive load during critical task activities and learning. Affective factors such as arousal and valence can be experienced at the same time, induced by the task in hand or by personal feelings. Identifying modalities or features that ... Microblog is a prominent information platform for sharing experiences, discussing current events, and exchanging ideas. Many events are first reported in social media, and increas- ing amounts of rich-media content are associated with the posts, making ... The promise of spectral clustering is that it can help detect complex shapes and intrinsic manifold structure in large and high dimensional spaces. The price for this promise is the computational cost O(n^3) for computing the eigen-decomposition of the ... We extend the Bayesian skill rating system of TrueSkill to accommodate score-based match outcomes. TrueSkill has proven to be a very effective algorithm for matchmaking --- the process of pairing competitors based on similar skill-level --- in ... Introduction More and more textual eHealth information is electronically available. Examples include scientific literature, care guidelines, health records, and social media. Language technologies (LTs) provide a way to analyse these documents for the... Introduction. Failures in information flow from clinical handover are the leading cause of sentinel events in the USA and associated with nearly half of all adverse events and over a tenth of preventable adverse events in Australia.1-3 Verbal clinical ... Introduction Invasive fungal diseases (IFDs) cause more than 1,000 deaths in hospitals and cost the health system more than AUD100m in Australia each year.1 The most common life-threatening IFD is aspergillosis and a patient with this IFD typically has ... CLEFeHealth2012 is the CLEF2012 workshop on cross-language evaluation of methods, applications, and resources for eHealth document analysis. Its focus is on written and spoken natural-language processing with the use scenario of people using ICT tools to ... Capabilities to share, integrate, and compare eHealth data, clinical trial results, and other evaluation outcomes together with eHealth applications are critical to accelerate discovery and its diffusion to clinical practice. However, the same ethical and... Classical mechanism design assumes that an agent's value of any determined outcome depends only on its private information. However in many situations, an agent's value of an outcome depends on the private information of other agents in addition to its ... The recently proposed ImageNet dataset consists of several million images, each annotated with a single object category. These annotations may be imperfect, in the sense that many images contain multiple objects belonging to the label vocabulary. In ... On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off It has been previously noted that optimization of the ncall@k relevance objective (i.e., a set-based objective that is 1 if at least n documents in a set of k are relevant, otherwise 0) encourages more result set diversification for smaller n, but ... |