Geometric and information-theoretic approaches to high-dimensional search

Student thesis: Doctoral Thesis (DSc)

This thesis comprises a brief introduction along with a presentation of ten selected research papers, the primary author of each being the candidate.

Cite this

Research output
Hilbert exclusion: improved metric search through finite isometric embeddings
Research output: Contribution to journal › Article › peer-review
High-dimensional simplexes for supermetric search
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Sampled angles in high-dimensional spaces
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
A Ptolemaic partitioning mechanism
Research output: Chapter in Book/Report/Conference proceeding › Chapter
nSimplexZen: a novel dimensionality reduction for Euclidean and Hilbert spaces
Research output: Contribution to journal › Article › peer-review
Correlations of cross-entropy loss in machine learning
Research output: Contribution to journal › Article › peer-review
Supermetric search
Research output: Contribution to journal › Article › peer-review
A bounded distance metric for comparing tree structure
Research output: Contribution to journal › Article › peer-review
On the application of convex transforms to metric search
Research output: Contribution to journal › Article › peer-review
Similarity search with multiple-object queries
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

'