11 accepted papers
Tool-mediated interactions enable robotics to manipulate and explore granular objects, producing informative auditory signals. A central challenge is transferring this perceptual knowledge across different tools and behaviors without costly data collection for each new context. We address this probl…
We pursue tractable Bayesian analysis of generalized linear models (GLMs) for categorical data. GLMs have been difficult to scale to more than a few dozen categories due to non-conjugacy or strong posterior dependencies when using conjugate auxiliary variable methods. We define a new class of GLMs f…
Early warning prediction systems can suffer from high false alarm rates that limit utility, especially in settings with high class imbalance such as healthcare. Despite the widespread need to control false alarms, the dominant classifier training paradigm remains minimizing cross entropy, a loss fun…
Many medical decision-making tasks can be framed as partially observed Markov decision processes (POMDPs). However, prevailing two-stage approaches that first learn a POMDP and then solve it often fail because the model that best fits the data may not be well suited for planning. We introduce a new…
Supervisory signals can help topic models discover low-dimensional data representations which are useful for a specific prediction task. We propose a framework for training supervised latent Dirichlet allocation that balances two goals: faithful generative explanations of high-dimensional data and a…
Confocal endomicroscopy can be used for identification of early mucosal dysplasia in various gastrointestinal conditions, and has particular potential in the monitoring of Barrett's oesophagus and the early stages of oesophageal cancer. However, it can be difficult to systematically scan a significa…
Robot-assisted minimally invasive surgery can benefit from the automation of common, repetitive or well-defined but ergonomically difficult tasks. One such task is the scanning of a pick-up endomicroscopy probe over a complex, undulating tissue surface to enhance the effective field-of-view through…
Effective in situ, in vivo tumour margin assessment is an important, yet unmet, clinical demand in surgical oncology. Recent advances in probe-based optical imaging tools such as confocal endomicroscopy is making inroads in clinical applications. In practice, maintaining consistent tissue contact wh…
The surgical robotics community have developed many different flexible robot designs to address the access problems of minimally invasive surgery. In this paper, we present a hand-held mechatronic tool with a miniaturized distal flexible manipulator incorporating a microscopy probe, camera and a lig…
Transanal Endoscopic Microsurgery (TEM) is a minimally invasive oncological resection procedure that utilises a natural orifice approach rather than the traditional abdominal or open approach. However, TEM has a significant recurrence rate due to incomplete excisions, which can possibly be attribute…
We introduce a new variational inference objective for hierarchical Dirichlet process admixture models. Our approach provides novel and scalable algorithms for learning nonparametric topic models of text documents and Gaussian admixture models of image patches. Improving on the point estimates of to…