Sökning: "Graph Data"

Visar resultat 11 - 15 av 239 avhandlingar innehållade orden Graph Data.

  1. 11. Sparse Voxel DAGs for Shadows and for Geometry with Colors

    Författare :Dan Dolonius; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; directed acyclic graph; octree; compression; voxel; geometry; shadows; colors;

    Sammanfattning : Triangles are probably the most common format for shapes in computer graphics. Nevertheless, when high detail is desired, Sparse Voxel Octrees (SVO) and Sparse Voxel Directed Acyclic Graphs (DAG) can be considerably more memory efficient. One of the first practical use cases for DAGs was to use the structure to represent precomputed shadows. LÄS MER

  3. 12. Graph Propositionalization for Learning from Structured Data

    Författare :Thashmee Karunaratne; Stockholms universitet; []
    Nyckelord :data- och systemvetenskap; Computer and Systems Sciences;

    Sammanfattning : Learning from structured data is challenging in terms of learning concepts, patterns or relations hidden within the structured data. The state-of-the-art methods include logic based approaches and graph based approaches. LÄS MER

  4. 13. Applications of Machine Learning on Natural Language Processing and Biomedical Data

    Författare :Dennis Medved; Institutionen för datavetenskap; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : Machine learning is ubiquitous in today’s society, with promising applicationsin the field of natural language processing (NLP), so that computers can handlehuman language better, and within the medical community, with the promiseof better treatments. Machine learning can be seen as a subfield of artificialintelligence (AI), where AI is used to describe a machine that mimics cognitivefunctions that humans associate with other human minds, such as learning orproblem solving. LÄS MER

  5. 14. Algorithmic Graph Problems - From Computer Networks to Graph Embeddings

    Författare :Martin Wahlén; Data Vetenskap; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Approximation Algorithms; Exact Algorithms; Time Complexity; Broadcasting;

    Sammanfattning : This dissertation is a contribution to the knowledge of the computational complexity of discrete combinatorial problems. 1. The first problem that we consider is to compute the maximum independent set of a box graph, that is, given a set of orthogonal boxes in the plane compute the largest subset such that no boxes in the subset overlap. LÄS MER

  7. 15. On practical machine learning and data analysis

    Författare :Daniel Gillblad; Anders Lansner; Finn Jensen; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Computer science; Datalogi;

    Sammanfattning : This thesis discusses and addresses some of the difficulties associated with practical machine learning and data analysis. Introducing data driven meth- ods in e. g. industrial and business applications can lead to large gains in productivity and efficiency, but the cost and complexity are often overwhelm- ing. LÄS MER