Output details
11 - Computer Science and Informatics
University of Birmingham
Output title
Compressed Fisher Linear Discriminant Analysis: Classification of Randomly Projected Data
Type
E - Conference contribution
Name of conference/published proceedings
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2010)
Volume number
-
Issue number
-
First page of article
1119
ISSN of proceedings
-
Year of publication
2010
URL
-
Number of additional authors
1
Additional information
<24>Paper accepted for oral presentation in a top venue with acceptance rate 17% (13% oral). Proves that generalisation of a Fisher Linear Discriminant classifier can be achieved in randomly projected data spaces of dimension O(log #classes). This is a sharp improvement on O(log #points) previously known for margin based classifiers. Follow-on version won an IBM Best Student Paper Award at ICPR'10, with invited extension in Pattern Recognition Letters ICPR10 Awards Special Issue. It led to Kaban invited to speak at SIMPLE'12 workshop at MPI Dresden. Related ideas applied to optimisation (Kaban et al.) won a best paper award at GECCO'13.
Interdisciplinary
-
Cross-referral requested
-
Research group
B - Natural Computation
Citation count
3
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
