Episodic Multi-Task Learning with Heterogeneous Neural Processes

This paper focuses on the data-insufficiency problem in multi-task learning within an episodic training setup. Specifically, we explore the potential of heterogeneous information across tasks and meta-knowledge among episodes to effectively tackle each task with limited data. Existing meta-learning methods often fail to take advantage of crucial heterogeneous information in a single episode, while multi-task learning models neglect reusing experience from earlier episodes. To address the problem of insufficient data, we develop Heterogeneous Neural Processes (HNPs) for the episodic multi-task setup. Within the framework of hierarchical Bayes, HNPs effectively capitalize on prior experiences as meta-knowledge and capture task-relatedness among heterogeneous tasks, mitigating data-insufficiency. Meanwhile, transformer-structured inference modules are designed to enable efficient inferences toward meta-knowledge and task-relatedness. In this way, HNPs can learn more powerful functional priors for adapting to novel heterogeneous tasks in each meta-test episode. Experimental results show the superior performance of the proposed HNPs over typical baselines, and ablation studies verify the effectiveness of the designed inference modules.Comment: 28 pages, spotlight of NeurIPS 202

Addressing Risk Governance Deficits through Scenario Modeling Practices

In a world of inevitable regret, those governing risk must build practices that withstand the vicissitudes of actual events by demonstrating that reasonable efforts had been and will continue to be taken despite those harms. However, what is reasonable depends on one’s worldview, and so not giving different worldviews appropriate consideration leads to deficits in the quality of risk governance. This project developed foresight methods for eliciting, discovering, representing, and modeling scenarios which capture the counterfactual forests created by disparate worldviews. These methods employ structural differences between objective and subjective relations toward physical events to delineate the actual points of contention, while maintaining neutrality by remaining strictly grounded in the input of the stakeholders themselves. These methods respect how people frame causal information psychologically, avoiding biases known to affect political judgment. Overall, these methods serve as a reminder that how we ask designs how we think. ii

Youth, training and the training state : the real history of youth training in the twentieth century

This work provides an explanation for the existence of youth that goes beyond the analysis presented by the mainstream sociology of youth and its critics. This involves not only a deconstruction of the sociology of youth, but also a deconstruction of the nature of reality which it supports. I undermine this reality by utilising a theory of abstraction developed by Karl Marx initially from his work on alienated labour and later through his theory of commodity fetishism. Following Marx I suggest that the real world is in fact an abstract (virtual) reality. As part of that reality youth is an abstraction which exists in a concrete form. I trace the development of this abstraction to its manifestation in its most modern form as youth. I suggest that youth has always existed, but not as youth. I argue that the modern form of youth was derived in 1948 as the product of a particular configuration of the productive consumption between capital and labour. I explore the development of this relationship as it manifests itself in its various youthful forms (: Elvis-the teenager... punk) and through a particular regulatory device (: the training state). I conclude that there is no future for youth as youth, by which I mean there is no work, by which I mean there is no money, by which I mean there is no adulthood, by which I mean there is no responsibility, only not responsibility. I suggest that the sociology of youth, and in particular the work of the cultural theorists, e. g. S. Hall, and the practical policies that it supports are, in fact, condemning youth to its existence as youth, for which there is no future. Although the subject matter of the work is youth I am also concerned with the nature of my own subjectivity. This concern includes my own subjectivity as a co-operating employee of the training state and as a subject involved in academic research. I become what I am: an immanent part of the social reality I am trying to explain. This incursion denies the detached perspective of social science and demands a critique of its methodology which I support with reference to painterly (: Cubist) and scientific theories of relativity. I connect these more complete explanations of the real world with Marx's own theory of relativity: the law of value. This engagement with relativity enables me to investigate the determined forms of social existence, e. g. time, space, subjectivity, youth and social life itself, beyond these determinations and, therefore, beyond the future

Vocational technical and adult education: Status, trends and issues related to electronic delivery

Data are analyzed, and trends and issues are discussed to provide information useful to the systems designer who wishes to identify and assess the opportunities for large scale electronic delivery in vocational/technical and adult education. Issues connected with vocational/technical education are investigated, with emphasis on those issues in the current spotlight which are relevant to the possibilities of electronic delivery. The current role of media is examined in vocational/technical instruction

Two studies in resource-efficient inference: structural testing of networks, and selective classification

Inference systems suffer costs arising from information acquisition, and from communication and computational costs of executing complex models. This dissertation proposes, in two distinct themes, systems-level methods to reduce these costs without affecting the accuracy of inference by using ancillary low-cost methods to cheaply address most queries, while only using resource-heavy methods on 'difficult' instances. The first theme concerns testing methods in structural inference of networks and graphical models, the proposal being that one first cheaply tests whether the structure underlying a dataset differs from a reference structure, and only estimates the new structure if this difference is large. This study focuses on theoretically establishing separations between the costs of testing and learning to determine when a strategy such as the above has benefits. For two canonical models---the Ising model, and the stochastic block model---fundamental limits are derived on the costs of one- and two-sample goodness-of-fit tests by determining information-theoretic lower bounds, and developing matching tests. A biphasic behaviour in the costs of testing is demonstrated: there is a critical size scale such that detection of differences smaller than this size is nearly as expensive as recovering the structure, while detection of larger differences has vanishing costs relative to recovery. The second theme concerns using Selective classification (SC), or classification with an option to abstain, to control inference-time costs in the machine learning framework. The proposal is to learn a low-complexity selective classifier that only abstains on hard instances, and to execute more expensive methods upon abstention. Herein, a novel SC formulation with a focus on high-accuracy is developed, and used to obtain both theoretical characterisations, and a scheme for learning selective classifiers based on optimising a collection of class-wise decoupled one-sided risks. This scheme attains strong empirical performance, and admits efficient implementation, leading to an effective SC methodology. Finally, SC is studied in the online learning setting with feedback only provided upon abstention, modelling the practical lack of reliable labels without expensive feature collection, and a Pareto-optimal low-error scheme is described

Trans Affects: Performance, Technology, and the Racialization of Femininity

Recognizing performance and technology as entangled modes of bodily expression, Trans Affects: Performance, Technology, and the Racialization of Femininity examines how Western tropes of Asian and Asian American femininity continue to shape differently sexed and gendered bodies. Drawing on Asian and Asian American artists in relation to U.S. contexts, this study enacts close readings of performances of hypersexuality, drag, and the trans body as they intersect with photography, Internet culture, multimedia installations, viral videos, biomedia, and emerging technologies. Specifically, the dissertation focuses on four contemporary artists: Laurel Nakadate, Ming Wong, Luo, and Yozmit. Employing “trans” as a theoretical lens to highlight affective capacities of art, I argue that “trans affects” in these performances resist the binary choice to either reject tropes or accept them as totalizing. The set of artists I explore do not engage in direct opposition to the stereotypes or tropes forwarded by processes of racialized femininity. Instead, they operate in more diffuse modes of affirmation, destabilization, confusion, and play, pointing to the possibilities that indeterminacy might offer politics and ethics. Trans affects accounts for the temporal crossings of affect and the political resistances of trans. As such, trans affects offers modes both of reading and politics. This study employs critical cultural methodologies, historically situating contemporary medial performances in cultural, linguistic, and political context. Through critical race/ethnic studies, queer theory, trans studies, and feminist theory, this interdisciplinary project demonstrates how performing and media-making might counter dominant normativizing modes of representation. Where scholarship on performance and technology has tended to eschew connections amongst race, gender, and sexuality, this project advances a comparative account of transnational racialized femininity in women, men, and those who defy the gender/sex binary. Moreover, where Asian and Asian American gender and sexuality studies have tended to focus on problems of representation, this dissertation offers tactics for resistance.Doctor of Philosoph