title: Pruning feature extractor stacking for cross-domain few-shot learning

authors: Wang, Hongyu

subjects: computer science

abstract: Combining knowledge from source domains to learn efficiently from a few labelled instances in a target domain is a transfer learning problem known as cross-domain few-shot learning (CDFSL). Feature extractor stacking (FES) is a state-of-the-art CDFSL method that maintains a collection of source domain feature extractors instead of a single universal extractor. FES uses stacked generalisation to build an ensemble from extractor snapshots saved during target domain fine-tuning. It outperforms several contemporary universal model-based CDFSL methods in the Meta-Dataset benchmark. However, it incurs higher storage cost because it saves a snapshot for every fine-tuning iteration for every extractor. In this work, we propose a bidirectional snapshot selection strategy for FES, leveraging its cross-validation process and the ordered nature of its snapshots, and demonstrate that a 95% snapshot reduction can be achieved while retaining the same level of accuracy.

text: Pruning feature extractor stacking for cross-domain few-shot learning Combining knowledge from source domains to learn efficiently from a few labelled instances in a target domain is a transfer learning problem known as cross-domain few-shot learning (CDFSL). Feature extractor stacking (FES) is a state-of-the-art CDFSL method that maintains a collection of source domain feature extractors instead of a single universal extractor. FES uses stacked generalisation to build an ensemble from extractor snapshots saved during target domain fine-tuning. It outperforms several contemporary universal model-based CDFSL methods in the Meta-Dataset benchmark. However, it incurs higher storage cost because it saves a snapshot for every fine-tuning iteration for every extractor. In this work, we propose a bidirectional snapshot selection strategy for FES, leveraging its cross-validation process and the ordered nature of its snapshots, and demonstrate that a 95% snapshot reduction can be achieved while retaining the same level of accuracy.

year: 2025

title: Sad or happy? The effects of emotions on stated preferences for environmental goods

authors: Hanley, Nick

subjects: Choice experiments

abstract: A substantial literature in behavioural science and psychology shows that emotions affect human choices and values. This paper investigates whether such emotional impacts are also present in stated choice experiments for environmental goods. If this were so, it would introduce an additional element of context dependence to the welfare measures derived from such methods, and would be at odds with the rational choice model underlying welfare economics. A laboratory experiment using three different emotion treatments was combined with a stated preference choice experiment concerned with changes in coastal water quality and fish populations in New Zealand. No statistically significant effects of changes in emotional state on estimated preference parameters, willingness to pay or the randomness of choices were found. The paper concludes by questioning, why such a contrast exists with empirical findings in behavioural science.

text: Sad or happy? The effects of emotions on stated preferences for environmental goods A substantial literature in behavioural science and psychology shows that emotions affect human choices and values. This paper investigates whether such emotional impacts are also present in stated choice experiments for environmental goods. If this were so, it would introduce an additional element of context dependence to the welfare measures derived from such methods, and would be at odds with the rational choice model underlying welfare economics. A laboratory experiment using three different emotion treatments was combined with a stated preference choice experiment concerned with changes in coastal water quality and fish populations in New Zealand. No statistically significant effects of changes in emotional state on estimated preference parameters, willingness to pay or the randomness of choices were found. The paper concludes by questioning, why such a contrast exists with empirical findings in behavioural science.

year: 2017

title: Putting the draft learning progression framework - Maori in the New Zealand Curriculum - to work: An Illustration

authors: Johnson, Diane

subjects: Māori language education

abstract: How language curricula are implemented in the classroom is of critical importance. Here, we take one achievement objective from the draft Learning Progression Framework for Māori in mainstream classes and demonstrate one way in which it can be realised as a core integrated skills lesson, that is, as a lesson that introduces new language (core lesson) through all four skills - reading, writing, listening and speaking (an integrated skills lesson). The lesson is preceded by a discussion of the type of planning that accompanies the implementation of language curricula.

text: Putting the draft learning progression framework - Maori in the New Zealand Curriculum - to work: An Illustration How language curricula are implemented in the classroom is of critical importance. Here, we take one achievement objective from the draft Learning Progression Framework for Māori in mainstream classes and demonstrate one way in which it can be realised as a core integrated skills lesson, that is, as a lesson that introduces new language (core lesson) through all four skills - reading, writing, listening and speaking (an integrated skills lesson). The lesson is preceded by a discussion of the type of planning that accompanies the implementation of language curricula.

year: 2003-09