Search for dissertations about: "Mathematics and Learning"

Showing result 1 - 5 of 222 swedish dissertations containing the words Mathematics and Learning.

  2. 1. Children’s early mathematics learning and development : Number game interventions and number line estimations

    Author : Jessica Elofsson; Ulf Träff; Joakim Samuelsson; Stefan Gustafson; Camilla Björklund; Linköpings universitet; []
    Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; mathematics learning and development; number knowledge and skills; intervention; number games; number line estimation; representations of number; lärande och utveckling i matematik; numeriska kunskaper och färdigheter; intervention; numeriska spel; skattningar av tal på tallinjer; representationer av tal.;

    Abstract : Children’s early mathematics learning and development have become a topic of increasing interest over the past decade since early mathematical knowledge and skills have been shown to be a strong predictor of later mathematics performance. Understanding how children develop mathematical knowledge and skills and how they can be supported in their early learning could thus prove to be a vital component in promoting learning of more formal mathematics. READ MORE

  4. 2. Position Estimation in Uncertain Radio Environments and Trajectory Learning

    Author : Yuxin Zhao; Fredrik Gunnarsson; Fredrik Gustafsson; Carsten Fritsche; Henk Wymeersch; Linköpings universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES;

    Abstract : To infer the hidden states from the noisy observations and make predictions based on a set of input states and output observations are two challenging problems in many research areas. Examples of applications many include position estimation from various measurable radio signals in indoor environments, self-navigation for autonomous cars, modeling and predicting of the traffic flows, and flow pattern analysis for crowds of people. READ MORE

  5. 3. Information-Theoretic Generalization Bounds: Tightness and Expressiveness

    Author : Fredrik Hellström; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; information theory; neural networks; generalization; statistical learning; meta learning; PAC-Bayes; Machine learning;

    Abstract : Machine learning has achieved impressive feats in numerous domains, largely driven by the emergence of deep neural networks. Due to the high complexity of these models, classical bounds on the generalization error---that is, the difference between training and test performance---fail to explain this success. READ MORE

  6. 4. Reinforcement Learning and Dynamical Systems

    Author : Björn Lindenberg; Karl-Olof Lindahl; Marc G. Bellemare; Linnéuniversitetet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; artificial intelligence; distributional reinforcement learning; Markov decision processes; Bellman operators; deep learning; multi-armed bandits; Bayesian bandits; conjugate priors; Thompson sampling; linear finite dynamical systems; cycle orbits; fixed-point systems; Mathematics; Matematik; Computer Science; Datavetenskap;

    Abstract : This thesis concerns reinforcement learning and dynamical systems in finite discrete problem domains. Artificial intelligence studies through reinforcement learning involves developing models and algorithms for scenarios when there is an agent that is interacting with an environment. READ MORE

  7. 5. Network Parameterisation and Activation Functions in Deep Learning

    Author : Martin Trimmel; Matematik LTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; deep learning; linear region; network parameterisation; activation function; network calibration; conformal predictnio; tropical algebra; rational function; temperature scaling; network symmetries;

    Abstract : Deep learning, the study of multi-layered artificial neural networks, has received tremendous attention over the course of the last few years. Neural networks are now able to outperform humans in a growing variety of tasks and increasingly have an impact on our day-to-day lives. READ MORE