Zero-Shot Deep Domain Adaptation

Domain adaptation is an important tool to transfer knowledge about a task (e.g. classification) learned in a source domain to a second, or target domain. Current approaches assume that task-relevant target-domain data is available during training. We demonstrate how to perform domain adaptation when no such task-relevant target-domain data is available. To tackle this issue, we propose zero-shot deep domain adaptation (ZDDA), which uses privileged information from task-irrelevant dual-domain pairs. ZDDA learns a source-domain representation which is not only tailored for the task of interest but also close to the target-domain representation. Therefore, the source-domain task of interest solution (e.g. a classifier for classification tasks) which is jointly trained with the source-domain representation can be applicable to both the source and target representations. Using the MNIST, Fashion-MNIST, NIST, EMNIST, and SUN RGB-D datasets, we show that ZDDA can perform domain adaptation in classification tasks without access to task-relevant target-domain training data. We also extend ZDDA to perform sensor fusion in the SUN RGB-D scene classification task by simulating task-relevant target-domain representations with task-relevant source-domain data. To the best of our knowledge, ZDDA is the first domain adaptation and sensor fusion method which requires no task-relevant target-domain data. The underlying principle is not particular to computer vision data, but should be extensible to other domains.Comment: This paper is accepted to the European Conference on Computer Vision (ECCV), 201

A first step toward cognitive remediation of voices: a case study.

Several studies have shown that source-monitoring errors are related to verbal hallucinations in schizophrenia. An exploratory pilot study has been carried out to investigate the possibility of training patients in how to avoid errors in source-monitoring. One patient with paranoid schizophrenia and persistent thought insertions was trained for 6 hours to use mnemonic techniques to compensate specific deficits in source-monitoring. Results show that the patient was able to improve his performance and maintain the acquired progress at a 1-month follow-up assessment. These preliminary results are interesting for developing a larger controlled study of cognitive remediation of source-monitoring deficits

Predictive processing and source monitoring in the psychosis continuum

Schizophrenia is a serious and debilitating mental illness, and sufferers frequently experience a multitude of symptoms. Of particular interest to the current Thesis are psychotic symptoms including delusions, hallucinations and associated self- disturbances such as interference in the agency and ownership of thoughts and actions. Since the disorder was first described over a century ago, research into the pathogenesis of schizophrenia has advanced greatly. However, there are still large gaps in the current knowledge and understanding of the neuropsychological bases of this devastating illness. The current Thesis adopts a cognitive neuropsychiatric approach and applies a continuum model to the construct of psychosis. The aim of the current Thesis was to incorporate theories such as the source monitoring and the predictive processing frameworks across a range of behavioural tasks, in order to investigate some of the neuropsychological deficits in schizotypy and early psychotic symptoms. Healthy individuals with schizotypal traits and patients with early psychosis who did not yet meet a full diagnosis of schizophrenia underwent a battery of behavioural paradigms, with each task aimed at a different aspect of predictive processing and source monitoring. In healthy individuals, nonclinical psychosis-like experiences measured with schizotypy scales were significantly associated with difficulties in the source monitoring of actions, in particular deficits in reality monitoring and internal source monitoring. However, no significant relationships were found for the predictive processing tasks, which focused on the perceptual (force-matching), associative (Kamin blocking) and motivational (reversal learning) domains. In the patients with first episode psychosis, positive psychotic symptoms were not significantly correlated with specific deficits in either category of tasks, although this study was under- powered and strong conclusion could not be drawn. Nevertheless, these findings have provided support for partial dimensionality in psychosis vulnerability and will serve as foundations for future research on a larger scale

The Visual Experience of Kinds

Do perceiving subjects represent kind properties in the content of their conscious visual experience when they see and recognize instances of those natural kinds? In Part 1 of my thesis I clarify this question, in Part 2 I answer it, and in Part 3 I raise a problem for previous answers. Part 1 conceives of conscious experience in an internalist way, and the unified conscious episode does not exclude having beliefs about what one sees. Following Siegel (2006) and Bayne (2011), Part 2 formulates two arguments in support of representing kind properties in the content of experience. In Part 3, I argue that attempts to distinguish visual experiences from visual beliefs might fail to account for the interplay of sensory and cognitive elements in visual object recognition. I conclude by suggesting it has not been established that visual experiences can be distinguished from visual beliefs