6 citations · 7 across the 6 of their papers we have counts for
4 papers · 1 filter
Federated Attention Autoencoders with a Stochastic Aggregation Scheme for Anomaly Detection
Mihailo Ilić, Miloš Savić, Vladimir Kurbalija +3
Outlier detection in decentralized data environments is a challenging task for many machine learning implementations, particularly in settings where data cannot be shared. Recently…
Attention, Anomalies! Handling Attention Layers in Unsupervised Federated Outlier Detection
Mihailo Ilić, Miloš Savić, Vladimir Kurbalija +3
Attention layers are the backbone of today's most powerful and impactful models. Models with multi-million and billion parameters rely on contextual knowledge provided by attention…
Hub-aware Random Walk Graph Embedding Methods for Classification
Aleksandar Tomčić, Miloš Savić, Miloš Radovanović
In the last two decades we are witnessing a huge increase of valuable big data structured in the form of graphs or networks. To apply traditional machine learning and data analytic…
Local Intrinsic Dimensionality Measures for Graphs, with Applications to Graph Embeddings
Miloš Savić, Vladimir Kurbalija, Miloš Radovanović
The notion of local intrinsic dimensionality (LID) is an important advancement in data dimensionality analysis, with applications in data mining, machine learning and similarity se…