title: Sampling-based Prediction of Algorithm Runtime

authors: Sun, Quan

subjects: machine learning

abstract: The ability to handle and analyse massive amounts of data has been progressively improved during the last decade with the growth of computing power and the opening up of the Internet era. Nowadays, machine learning algorithms have been widely applied in various fields of engineering sciences and in real world applications. However, currently, users of machine learning algorithms do not usually receive feedback on when a given algorithm will have finished building a model for a particular data set. While in theory such estimation can be obtained by asymptotic performance analysis, the complexity of machine learning algorithms means theoretical asymptotic performance analysis can be a very difficult task. This work has two goals. The first goal is to investigate how to use sampling-based techniques to predict the running time of a machine learning algorithm training on a particular data set. The second goal is to empirically evaluate a set of sampling-based running time prediction methods. Experimental results show that, with some care in the sampling stage, application of appropriate transformations on the running time observations followed by the use of suitable curve fitting algorithms makes it possible to obtain useful average-case running time predictions and an approximate time function for a given machine learning algorithm building a model on a particular data set. There are 41 WEKA (Witten  Frank, 2005) machine learning algorithms are used for the experiments.

text: Sampling-based Prediction of Algorithm Runtime The ability to handle and analyse massive amounts of data has been progressively improved during the last decade with the growth of computing power and the opening up of the Internet era. Nowadays, machine learning algorithms have been widely applied in various fields of engineering sciences and in real world applications. However, currently, users of machine learning algorithms do not usually receive feedback on when a given algorithm will have finished building a model for a particular data set. While in theory such estimation can be obtained by asymptotic performance analysis, the complexity of machine learning algorithms means theoretical asymptotic performance analysis can be a very difficult task. This work has two goals. The first goal is to investigate how to use sampling-based techniques to predict the running time of a machine learning algorithm training on a particular data set. The second goal is to empirically evaluate a set of sampling-based running time prediction methods. Experimental results show that, with some care in the sampling stage, application of appropriate transformations on the running time observations followed by the use of suitable curve fitting algorithms makes it possible to obtain useful average-case running time predictions and an approximate time function for a given machine learning algorithm building a model on a particular data set. There are 41 WEKA (Witten  Frank, 2005) machine learning algorithms are used for the experiments.

year: 2009

title: Complementarity of spike- and rate-based dynamics of neural systems

authors: Wilson, Marcus T.

subjects: neurons

abstract: Relationships between spiking-neuron and rate-based approaches to the dynamics of neural assemblies are explored by analyzing a model system that can be treated by both methods, with the rate-based method further averaged over multiple neurons to give a neural-field approach. The system consists of a chain of neurons, each with simple spiking dynamics that has a known rate-based equivalent. The neurons are linked by propagating activity that is described in terms of a spatial interaction strength with temporal delays that reflect distances between neurons; feedback via a separate delay loop is also included because such loops also exist in real brains. These interactions are described using a spatiotemporal coupling function that can carry either spikes or rates to provide coupling between neurons. Numerical simulation of corresponding spike- and rate-based methods with these compatible couplings then allows direct comparison between the dynamics arising from these approaches. The rate-based dynamics can reproduce two different forms of oscillation that are present in the spike-based model: spiking rates of individual neurons and network-induced modulations of spiking rate that occur if network interactions are sufficiently strong. Depending on conditions either mode of oscillation can dominate the spike-based dynamics and in some situations, particularly when the ratio of the frequencies of these two modes is integer or half-integer, the two can both be present and interact with each other.

text: Complementarity of spike- and rate-based dynamics of neural systems Relationships between spiking-neuron and rate-based approaches to the dynamics of neural assemblies are explored by analyzing a model system that can be treated by both methods, with the rate-based method further averaged over multiple neurons to give a neural-field approach. The system consists of a chain of neurons, each with simple spiking dynamics that has a known rate-based equivalent. The neurons are linked by propagating activity that is described in terms of a spatial interaction strength with temporal delays that reflect distances between neurons; feedback via a separate delay loop is also included because such loops also exist in real brains. These interactions are described using a spatiotemporal coupling function that can carry either spikes or rates to provide coupling between neurons. Numerical simulation of corresponding spike- and rate-based methods with these compatible couplings then allows direct comparison between the dynamics arising from these approaches. The rate-based dynamics can reproduce two different forms of oscillation that are present in the spike-based model: spiking rates of individual neurons and network-induced modulations of spiking rate that occur if network interactions are sufficiently strong. Depending on conditions either mode of oscillation can dominate the spike-based dynamics and in some situations, particularly when the ratio of the frequencies of these two modes is integer or half-integer, the two can both be present and interact with each other.

year: 2012

title: Redefining taonga: The Treaty Principles Bill and its potential impact on the status of te reo Māori

authors: Carter, Wayne Ngahuka

abstract: This thesis explores the potential impact of Aotearoa New Zealand’s proposed Treaty Principles Bill on the recognition and protection of te reo Māori (Māori language) as a taonga under the Treaty of Waitangi. This research examines the redefinition of fundamental Treaty principles as outlined in the bill, specifically addressing important questions concerning how the transition from partnership, protection and participation towards a focus in equal rights might influence both the legal standing and the cultural status of te reo Māori. With a quantitative methodology approach, this study draws from a range of sources, including legislative policies, political documents, historical records, and academic analysis, to evaluate the impacts and risks this bill could impose. A comparative analysis study with international examples of indigenous language protection provides broader insights into the potential effects on Māori language revitalisation efforts and te reo Māori and its status under the 2016 Māori Language Act. Early findings indicate that the Treaty Principles Bill has ignited considerable debate throughout Aotearoa New Zealand, emphasising tensions between traditional interpretations of the Treaty of Waitangi and framework proposed by the Act Party. Māori rights advocates and public debates express worries that the bill could diminish current protection and reduce advancements achieved for te reo Māori as a taonga. Critics argue that redefining these principles might fracture Māori-Crown relationships, possibly weakening differences and impacting New Zealand’s governance and national identity. This debate emphasises the challenging task of restoring New Zealand’s colonial past with its modern goals for fairness and equality. As Parliament reviews this legislation, it is confronted with a crucial decision that will influence the future direction of Aotearoa New Zealand.

text: Redefining taonga: The Treaty Principles Bill and its potential impact on the status of te reo Māori This thesis explores the potential impact of Aotearoa New Zealand’s proposed Treaty Principles Bill on the recognition and protection of te reo Māori (Māori language) as a taonga under the Treaty of Waitangi. This research examines the redefinition of fundamental Treaty principles as outlined in the bill, specifically addressing important questions concerning how the transition from partnership, protection and participation towards a focus in equal rights might influence both the legal standing and the cultural status of te reo Māori. With a quantitative methodology approach, this study draws from a range of sources, including legislative policies, political documents, historical records, and academic analysis, to evaluate the impacts and risks this bill could impose. A comparative analysis study with international examples of indigenous language protection provides broader insights into the potential effects on Māori language revitalisation efforts and te reo Māori and its status under the 2016 Māori Language Act. Early findings indicate that the Treaty Principles Bill has ignited considerable debate throughout Aotearoa New Zealand, emphasising tensions between traditional interpretations of the Treaty of Waitangi and framework proposed by the Act Party. Māori rights advocates and public debates express worries that the bill could diminish current protection and reduce advancements achieved for te reo Māori as a taonga. Critics argue that redefining these principles might fracture Māori-Crown relationships, possibly weakening differences and impacting New Zealand’s governance and national identity. This debate emphasises the challenging task of restoring New Zealand’s colonial past with its modern goals for fairness and equality. As Parliament reviews this legislation, it is confronted with a crucial decision that will influence the future direction of Aotearoa New Zealand.

year: 2025