activity
20192021
most citedMSTREAM: Fast Anomaly Detection in Multi-Aspect Streams

63 citations · 68 across the 6 of their papers we have counts for

collaborators

8 papers

cs.LG2021

SSMF: Shifting Seasonal Matrix Factorization

Koki Kawabata, Siddharth Bhatia, Rui Liu +2

Given taxi-ride counts information between departure and destination locations, how can we forecast their future demands? In general, given a data stream of events with seasonal pa…

cs.LG2021

GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs

Siddharth Bhatia, Yiwei Wang, Bryan Hooi +1

Finding anomalous snapshots from a graph has garnered huge attention recently. Existing studies address the problem using shallow learning mechanisms such as subspace selection, eg…

cs.DS2021★ 1 cited

Sketch-Based Anomaly Detection in Streaming Graphs

Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi +3

Given a stream of graph edges from a dynamic graph, how can we assign anomaly scores to edges and subgraphs in an online manner, for the purpose of detecting unusual behavior, usin…

cs.LG2021★ 1 cited

MemStream: Memory-Based Streaming Anomaly Detection

Siddharth Bhatia, Arjit Jain, Shivin Srivastava +2

Given a stream of entries over time in a multi-dimensional data setting where concept drift is present, how can we detect anomalous activities? Most of the existing unsupervised an…

cs.LG2021★ 1 cited

Isconna: Streaming Anomaly Detection with Frequency and Patterns

Rui Liu, Siddharth Bhatia, Bryan Hooi

An edge stream is a common form of presentation of dynamic networks. It can evolve with time, with new types of nodes or edges being continuously added. Existing methods for anomal…

cs.LG2020★ 2 cited

ExGAN: Adversarial Generation of Extreme Samples

Siddharth Bhatia, Arjit Jain, Bryan Hooi

Mitigating the risk arising from extreme events is a fundamental goal with many applications, such as the modelling of natural disasters, financial crashes, epidemics, and many oth…

cs.LG2020★ 63 cited

MSTREAM: Fast Anomaly Detection in Multi-Aspect Streams

Siddharth Bhatia, Arjit Jain, Pan Li +2

Given a stream of entries in a multi-aspect data setting i.e., entries having multiple dimensions, how can we detect anomalous activities in an unsupervised manner? For example, in…

cs.LG2019

MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams

Siddharth Bhatia, Bryan Hooi, Minji Yoon +2

Given a stream of graph edges from a dynamic graph, how can we assign anomaly scores to edges in an online manner, for the purpose of detecting unusual behavior, using constant tim…