Sevvandi Kandanaarachchi

Orcid: 0000-0002-0337-0395

According to our database1, Sevvandi Kandanaarachchi authored at least 18 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Extreme Value Modelling of Feature Residuals for Anomaly Detection in Dynamic Graphs.
CoRR, 2024

Graphons of Line Graphs.
CoRR, 2024

An Item Response Theory-based R Module for Algorithm Portfolio Analysis.
CoRR, 2024

Predicting the structure of dynamic graphs.
CoRR, 2024

Instance Space Analysis and Item Response Theory for Algorithm Testing.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2023
Comprehensive Algorithm Portfolio Evaluation using Item Response Theory.
J. Mach. Learn. Res., 2023

Detecting inner-LAN anomalies using hierarchical forecasting.
CoRR, 2023

DEFT: A New Distance-Based Feature Set for Keystroke Dynamics.
Proceedings of the 22nd International Conference of the Biometrics Special Interest Group, 2023

2022
Leave-One-Out Kernel Density Estimates for Outlier Detection.
J. Comput. Graph. Stat., January, 2022

Unsupervised anomaly detection ensembles using item response theory.
Inf. Sci., 2022

Honeyboost: Boosting honeypot performance with data fusion and anomaly detection.
Expert Syst. Appl., 2022

Anomaly detection in dynamic networks.
CoRR, 2022

Short-term prediction of stream turbidity using surrogate data and a meta-model approach.
CoRR, 2022

Benchmarking algorithm portfolio construction methods.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

2021
Dimension Reduction for Outlier Detection Using DOBIN.
J. Comput. Graph. Stat., 2021

2020
On normalization and algorithm selection for unsupervised outlier detection.
Data Min. Knowl. Discov., 2020

2019
Instance Space Analysis for Unsupervised Outlier Detection.
Proceedings of the 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning co-located with SIAM International Conference on Data Mining (SDM 2019), 2019

2016
Machine learning methods for predicting the outcome of hypervelocity impact events.
Expert Syst. Appl., 2016


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