Sökning: "learning problems in mathematics"

Visar resultat 21 - 25 av 80 avhandlingar innehållade orden learning problems in mathematics.

1. 21. Convergence and stability analysis of stochastic optimization algorithms

   Författare :Måns Williamson; Matematik LTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; numerical analysis; optimization; stochastic optimization; machine learning;

   Sammanfattning : This thesis is concerned with stochastic optimization methods. The pioneering work in the field is the article “A stochastic approximation algorithm” by Robbins and Monro [1], in which they proposed the stochastic gradient descent; a stochastic version of the classical gradient descent algorithm. LÄS MER

3. 22. Learning Computing at University: Participation and Identity : A Longitudinal Study

   Författare :Anne-Kathrin Peters; Arnold Pears; Anders Berglund; Anna Eckerdal; Lars Ulriksen; Uppsala universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; computing education research; engineering education research; computer science; higher education; engagement; diversity; equity; gender; competencies; culture; longitudinal; identity; participation; power; agency; uniformity; communities of practice; social theory of learning; phenomenography; student reflections; Datavetenskap med inriktning mot datavetenskapens didaktik; Computer Science with specialization in Computer Science Education Research;

   Sammanfattning : Computing education has struggled with student engagement and diversity in the student population for a long time. Research in science, technology, engineering, and mathematics (STEM) education suggests that taking a social, long-term perspective on learning is a fruitful approach to resolving some of these persistent challenges. LÄS MER

4. 23. Inverse Problems for Tumour Growth Models and Neural ODEs

   Författare :Rym Jaroudi; George Baravdish; Tomas Johansson; Jonas Unger; Gabriel Eilertsen; Lukáš Malý; Torbjörn Lundh; Linköpings universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

   Sammanfattning : This thesis concerns the application of methods and techniques from the theory of inverse problems and differential equations to study models arising in the areas of mathematical oncology and deep learning. The first problem studied is to develop methods to perform numerical simulations with full 3-dimensional brain imaging data of reaction-diffusion models for tumour growth forwards as well as backwards in time with the goal of enabling the numerical reconstruction of the source of the tumour given an image (or similar data) at a later stage in time of the tumour. LÄS MER

5. 24. Reliable Uncertainty Quantification in Statistical Learning

   Författare :David Widmann; Fredrik Lindsten; Dave Zachariah; Erik Sjöblom; Dino Sejdinovic; Uppsala universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Reliability; Calibration; Uncertainty; Probabilistic Model; Prediction; Julia; Machine learning; Maskininlärning;

   Sammanfattning : Mathematical models are powerful yet simplified abstractions used to study, explain, and predict the behavior of systems of interest. This thesis is concerned with their latter application as predictive models. LÄS MER

7. 25. Modes of Mathematical Modelling : An analysis of how modelling is used and interpreted in and out of school settings

   Författare :Peter Frejd; Christer Bergsten; Jonas Ärlebäck Bergman; Rudolf Strässer; Linköpings universitet; []
   Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES;

   Sammanfattning : The relevance of using mathematics in and for out-of-school activities is one main argument for teaching mathematics in education. Mathematical modelling is considered as a bridge between the mathematics learned and taught in schools and the mathematics used at the workplace and in society and it is also a central notion in the present Swedish mathematical syllabus for upper secondary school. LÄS MER