title: Feature extractor stacking for cross-domain few-shot learning

authors: Wang, Hongyu

subjects: cross-domain few-shot learning

abstract: Cross-domain few-shot learning (CDFSL) addresses learning problems where knowledge needs to be transferred from one or more source domains into an instance-scarce target domain with an explicitly different distribution. Recently published CDFSL methods generally construct a universal model that combines knowledge of multiple source domains into one feature extractor. This enables efficient inference but necessitates re-computation of the extractor whenever a new source domain is added. Some of these methods are also incompatible with heterogeneous source domain extractor architectures.

The first part of this thesis proposes feature extractor stacking (FES), a new CDFSL method for combining information from a collection of extractors, that can utilise heterogeneous pretrained extractors out of the box and does not maintain a universal model that needs to be re-computed when its extractor collection is updated. We present the basic FES algorithm, which is inspired by the classic stacked generalisation approach, and also introduce two variants: convolutional FES (ConFES) and regularised FES (ReFES). Given a target-domain task, these algorithms fine-tune each extractor independently, use cross-validation to extract training data for stacked generalisation from the support set, and learn a simple linear stacking classifier from this data. We evaluate our FES methods on the well-known Meta-Dataset benchmark, targeting image classification with convolutional neural networks, and show that they can achieve state-of-the-art performance.

The second part of this thesis proposes an efficient semi-supervised learning method that applies self-training to the classification head only and show that it can yield very consistent improvements in average performance in the Meta-Dataset benchmark for cross-domain few-shot learning when applied with FES and other contemporary methods utilising centroid-based classification.

The third part of this thesis proposes a bidirectional snapshot selection strategy for FES, leveraging its cross-validation process and the ordered nature of its snapshots, and demonstrates that a 95% snapshot reduction can be achieved while retaining the same level of accuracy.

text: Feature extractor stacking for cross-domain few-shot learning Cross-domain few-shot learning (CDFSL) addresses learning problems where knowledge needs to be transferred from one or more source domains into an instance-scarce target domain with an explicitly different distribution. Recently published CDFSL methods generally construct a universal model that combines knowledge of multiple source domains into one feature extractor. This enables efficient inference but necessitates re-computation of the extractor whenever a new source domain is added. Some of these methods are also incompatible with heterogeneous source domain extractor architectures.

The first part of this thesis proposes feature extractor stacking (FES), a new CDFSL method for combining information from a collection of extractors, that can utilise heterogeneous pretrained extractors out of the box and does not maintain a universal model that needs to be re-computed when its extractor collection is updated. We present the basic FES algorithm, which is inspired by the classic stacked generalisation approach, and also introduce two variants: convolutional FES (ConFES) and regularised FES (ReFES). Given a target-domain task, these algorithms fine-tune each extractor independently, use cross-validation to extract training data for stacked generalisation from the support set, and learn a simple linear stacking classifier from this data. We evaluate our FES methods on the well-known Meta-Dataset benchmark, targeting image classification with convolutional neural networks, and show that they can achieve state-of-the-art performance.

The second part of this thesis proposes an efficient semi-supervised learning method that applies self-training to the classification head only and show that it can yield very consistent improvements in average performance in the Meta-Dataset benchmark for cross-domain few-shot learning when applied with FES and other contemporary methods utilising centroid-based classification.

The third part of this thesis proposes a bidirectional snapshot selection strategy for FES, leveraging its cross-validation process and the ordered nature of its snapshots, and demonstrates that a 95% snapshot reduction can be achieved while retaining the same level of accuracy.

year: 2024

title: Technology education in New Zealand secondary schools: Time to realise future-focused and innovative practices.

authors: Reinsfield, Elizabeth

abstract: The official New Zealand Curriculum in technology education (MoE, 2007) counters past interpretations of the subject and provides opportunities for teachers to offer future-focused and innovative learning opportunities for all learners, regardless of their social or academic need. Teacher perceptions and the dominant discourse within a teaching community however, influence the way that professionals interpret, make meaning, and develop their professional identity or practice. This presentation will focus on the ways that technology teachers can work in partnership at an organisational level, to support professional ownership and change. It reports upon findings from research that explored how secondary technology teachers’ perceptions and interpretation of the curriculum impacted upon their knowledge for practice. The theoretical concepts include interpretivist and socio-cultural perspectives, as well as activity theory. The research was subjective in nature and designed to explore how understanding can be deduced from a participant’s actions, which are shaped and manifested in culturally meaningful ways. The presentation will propose threshold concepts that can support teachers to work towards learning-centred pedagogies, with a view to maximise the subject’s promise, in praxis.

text: Technology education in New Zealand secondary schools: Time to realise future-focused and innovative practices. The official New Zealand Curriculum in technology education (MoE, 2007) counters past interpretations of the subject and provides opportunities for teachers to offer future-focused and innovative learning opportunities for all learners, regardless of their social or academic need. Teacher perceptions and the dominant discourse within a teaching community however, influence the way that professionals interpret, make meaning, and develop their professional identity or practice. This presentation will focus on the ways that technology teachers can work in partnership at an organisational level, to support professional ownership and change. It reports upon findings from research that explored how secondary technology teachers’ perceptions and interpretation of the curriculum impacted upon their knowledge for practice. The theoretical concepts include interpretivist and socio-cultural perspectives, as well as activity theory. The research was subjective in nature and designed to explore how understanding can be deduced from a participant’s actions, which are shaped and manifested in culturally meaningful ways. The presentation will propose threshold concepts that can support teachers to work towards learning-centred pedagogies, with a view to maximise the subject’s promise, in praxis.

year: 2017

title: Indigenous children and youth: The case of marae courts in Aotearoa/New Zealand

authors: Toki, Valmaine

abstract: Marae2-based Courts are an initiative of the Judiciary that builds on existing programmes for offenders such as Te Whanau Awhina, and informed by the Koori Courts in Australia.3 This is the first time that a New Zealand court has conducted criminal cases on a Marae within the jurisdiction of the Youth Court. Most offenders referred to the programme are Maori4 and the process incorporates Maori tikanga (Maori customs).

text: Indigenous children and youth: The case of marae courts in Aotearoa/New Zealand Marae2-based Courts are an initiative of the Judiciary that builds on existing programmes for offenders such as Te Whanau Awhina, and informed by the Koori Courts in Australia.3 This is the first time that a New Zealand court has conducted criminal cases on a Marae within the jurisdiction of the Youth Court. Most offenders referred to the programme are Maori4 and the process incorporates Maori tikanga (Maori customs).

year: 2014