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Browsing by Subject "Machine learning"

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Browsing by Subject "Machine learning"

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  • Autonomously Learning About Meaningful Actions from Exploratory Behaviour 
    Newton, Heidi (Victoria University of Wellington, 2015)
    The thesis addresses the problem of creating an autonomous agent that is able to learn about and use meaningful hand motor actions in a simulated world with realistic physics, in a similar way to human infants learning to ...
  • Data-Driven Facial Expression Analysis from Live Video 
    Tay, Wee Kiat (Victoria University of Wellington, 2017)
    Emotion analytics is the study of human behavior by analyzing the responses when humans experience different emotions. In this thesis, we research into emotion analytics solutions using computer vision to detect emotions ...
  • Dirichlet Methods for Bayesian Source Detection in Radio Astronomy Images 
    Friedlander, Anna (Victoria University of Wellington, 2014)
    The sheer volume of data to be produced by the next generation of radio telescopes—exabytes of data on hundreds of millions of objects—makes automated methods for the detection of astronomical objects ("sources") essential. ...
  • Domain Adaptation and Domain Generalization with Representation Learning 
    Ghifary, Muhammad (Victoria University of Wellington, 2016)
    Machine learning has achieved great successes in the area of computer vision, especially in object recognition or classification. One of the core factors of the successes is the availability of massive labeled image or ...
  • Evolutionary Machine Learning for Classification with Incomplete Data 
    Tran, Cao Truong (Victoria University of Wellington, 2018)
    Classification is a major task in machine learning and data mining. Many real-world datasets suffer from the unavoidable issue of missing values. Classification with incomplete data has to be carefully handled because ...
  • Exploiting Latent Information in Recommender Systems 
    Zhang, Yun (Victoria University of Wellington, 2012)
    This thesis exploits latent information in personalised recommendation, and investigates how this information can be used to improve recommender systems. The investigations span three directions: scalar rating-based ...
  • Feature Manipulation with Genetic Programming 
    Neshatian, Kourosh (Victoria University of Wellington, 2010)
    Feature manipulation refers to the process by which the input space of a machine learning task is altered in order to improve the learning quality and performance. Three major aspects of feature manipulation are feature ...
  • Gaussian Processes for Regression and Optimisation 
    Boyle, Phillip (Victoria University of Wellington, 2007)
    Gaussian processes have proved to be useful and powerful constructs for the purposes of regression. The classical method proceeds by parameterising a covariance function, and then infers the parameters given the training ...
  • Genetic Programming for Classification with Unbalanced Data 
    Bhowan, Urvesh (Victoria University of Wellington, 2012)
    In classification,machine learning algorithms can suffer a performance bias when data sets are unbalanced. Binary data sets are unbalanced when one class is represented by only a small number of training examples (called ...
  • L'Arte Di Interazione Musicale: New Musical Possibilities Through Multimodal Techniques 
    Hochenbaum, Jordan Natan (Victoria University of Wellington, 2013)
    Multimodal communication is an essential aspect of human perception, facilitating the ability to reason, deduce, and understand meaning. Utilizing multimodal senses, humans are able to relate to the world in many ...
  • Learning Actions That Reduce Variation in Objects 
    Bebbington, James (Victoria University of Wellington, 2011)
    The variation in the data that a robot in the real world receives from its sensory inputs (i.e. its sensory data) will come from many sources. Much of this variation is the result of ground truths about the world, such as ...
  • Policy Direct Search for Effective Reinforcement Learning 
    Peng, Yiming (Victoria University of Wellington, 2019)
    Reinforcement Learning (RL) problems appear in diverse real-world applications and are gaining substantial attention in academia and industry. Policy Direct Search (PDS) is widely recognized as an effective approach to RL ...
  • Population-based Ensemble Learning with Tree Structures for Classification 
    Evans, Benjamin (Victoria University of Wellington, 2019)
    Ensemble learning is one of the most powerful extensions for improving upon individual machine learning models. Rather than a single model being used, several models are trained and the predictions combined to make a more ...
  • Resource and Performance Modelling of Hadoop Clusters Using Machine Learning 
    Tariq, Hassan (Victoria University of Wellington, 2020)
    There is a huge and rapidly increasing amount of data being generated by social media, mobile applications and sensing devices. Big data is the term usually used to describe such data and is described in terms of the 3Vs ...
  • SpaceSheets: Design Experimentation in Latent Space 
    Loh, Bryan (Victoria University of Wellington, 2018)
    Computational design tools enable designers to construct and manipulate representations of design artifacts to arrive at a solution. However, the constraints of deterministic programming impose a high cost of tedium and ...

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