50 citations · 128 across the 32 of their papers we have counts for
6 papers · 1 filter
Coverage-based Outlier Explanation
Yue Wu, Leman Akoglu, Ian Davidson
Outlier detection is a core task in data mining with a plethora of algorithms that have enjoyed wide scale usage. Existing algorithms are primarily focused on detection, that is th…
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification
Xuan Wu, Lingxiao Zhao, Leman Akoglu
Semi-supervised learning (SSL) is effectively used for numerous classification problems, thanks to its ability to make use of abundant unlabeled data. The main assumption of variou…
PairNorm: Tackling Oversmoothing in GNNs
Lingxiao Zhao, Leman Akoglu
The performance of graph neural nets (GNNs) is known to gradually decrease with increasing number of layers. This decay is partly attributed to oversmoothing, where repeated graph…
Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection
Xiaoyi Gu, Leman Akoglu, Alessandro Rinaldo
Nearest-neighbor (NN) procedures are well studied and widely used in both supervised and unsupervised learning problems. In this paper we are concerned with investigating the perfo…
Continual Rare-Class Recognition with Emerging Novel Subclasses
Hung Nguyen, Xuejian Wang, Leman Akoglu
Given a labeled dataset that contains a rare (or minority) class of of-interest instances, as well as a large class of instances that are not of interest, how can we learn to recog…
BuSCOPE : Fusing Individual & Aggregated Mobility Behavior for "Live" Smart City Services
Lakmal Meegahapola, Thivya Kandappu, Kasthuri Jayarajah +3
While analysis of urban commuting data has a long and demonstrated history of providing useful insights into human mobility behavior, such analysis has been performed largely in of…