12 citations · 22 across the 16 of their papers we have counts for
7 papers · 1 filter
Classification of Anomalies in Telecommunication Network KPI Time Series
Korantin Bordeau-Aubert, Justin Whatley, Sylvain Nadeau +2
The increasing complexity and scale of telecommunication networks have led to a growing interest in automated anomaly detection systems. However, the classification of anomalies de…
Dynamic Ensemble Size Adjustment for Memory Constrained Mondrian Forest
Martin Khannouz, Tristan Glatard
Supervised learning algorithms generally assume the availability of enough memory to store data models during the training and test phases. However, this assumption is unrealistic…
Reducing numerical precision preserves classification accuracy in Mondrian Forests
Marc Vicuna, Martin Khannouz, Gregory Kiar +2
Mondrian Forests are a powerful data stream classification method, but their large memory footprint makes them ill-suited for low-resource platforms such as connected objects. We e…
A benchmark of data stream classification for human activity recognition on connected objects
Martin Khannouz, Tristan Glatard
This paper evaluates data stream classifiers from the perspective of connected devices, focusing on the use case of HAR. We measure both classification performance and resource con…
High-Resolution Road Vehicle Collision Prediction for the City of Montreal
Antoine Hébert, Timothée Guédon, Tristan Glatard +1
Road accidents are an important issue of our modern societies, responsible for millions of deaths and injuries every year in the world. In Quebec only, in 2018, road accidents are…
Subject Cross Validation in Human Activity Recognition
Akbar Dehghani, Tristan Glatard, Emad Shihab
K-fold Cross Validation is commonly used to evaluate classifiers and tune their hyperparameters. However, it assumes that data points are Independent and Identically Distributed (i…