Miloš Radovanović

About Miloš Radovanović

Miloš Radovanović, With an exceptional h-index of 25 and a recent h-index of 19 (since 2020), a distinguished researcher at Univerzitet u Novom Sadu, specializes in the field of Computer Science, Data Mining, Text Mining, Web Mining, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Hub‐aware random walk graph embedding methods for classification

Dimensionality-Aware Outlier Detection: Theoretical and Experimental Analysis

Dimensionality-Aware Outlier Detection

Advanced CNN architectures for pollen classification: Design and comprehensive evaluation

Local intrinsic dimensionality measures for graphs, with applications to graph embeddings

Elastic distances for time-series classification: Itakura versus Sakoe-Chiba constraints

Intrinsic dimensionality estimation within tight localities: A theoretical and experimental analysis

Evaluation of LID-aware graph embedding methods for node clustering

Miloš Radovanović Information

University

Position

Associate Professor of Computer Science Serbia

Citations(all)

3108

Citations(since 2020)

1562

Cited By

2189

hIndex(all)

25

hIndex(since 2020)

19

i10Index(all)

50

i10Index(since 2020)

36

Email

University Profile Page

Google Scholar

Miloš Radovanović Skills & Research Interests

Computer Science

Data Mining

Text Mining

Web Mining

Machine Learning

Top articles of Miloš Radovanović

Hub‐aware random walk graph embedding methods for classification

Statistical Analysis and Data Mining: The ASA Data Science Journal

2024/4

Dimensionality-Aware Outlier Detection: Theoretical and Experimental Analysis

arXiv preprint arXiv:2401.05453

2024/1/10

Dimensionality-Aware Outlier Detection

2024

Advanced CNN architectures for pollen classification: Design and comprehensive evaluation

Applied Artificial Intelligence

2023/12/31

Local intrinsic dimensionality measures for graphs, with applications to graph embeddings

Information Systems

2023/10/1

Elastic distances for time-series classification: Itakura versus Sakoe-Chiba constraints

Knowledge and Information Systems

2022/10

Intrinsic dimensionality estimation within tight localities: A theoretical and experimental analysis

arXiv preprint arXiv:2209.14475

2022/9/29

Evaluation of LID-aware graph embedding methods for node clustering

2022/9/28

Contemporary research trends in computer science and informatics

2022

Local intrinsic dimensionality and graphs: Towards LID-aware graph embedding algorithms

2021/9/29

High Intrinsic Dimensionality Facilitates Adversarial Attack: Theoretical Evidence

IEEE Transactions on Information Forensics and Security

2021

Weighted kNN and constrained elastic distances for time-series classification

Expert Systems with Applications

2020/12/30

Graph-based metadata modeling in indoor positioning systems

Simulation Modelling Practice and Theory

2020/12/1

CAAVI-RICS model for observing the security of distributed IoT and edge computing systems

Simulation Modelling Practice and Theory

2020/12/1

An MQTT-based resource management framework for edge computing systems

2020/8/24

Time-series classification with constrained DTW distance and inverse-square weighted k-NN

2020/8/24

CAAVI-RICS model for analyzing the security of fog computing systems

2020

See List of Professors in Miloš Radovanović University(Univerzitet u Novom Sadu)

Co-Authors

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