We consider the problem of detecting anomalies in high arity categorical datasets. In most applications, anomalies are defined as data points that are 'abnormal'. Quite ...
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
Distributed systems are hard to build, profile, debug, and test. Monitoring a distributed system – to detect and analyze bugs, test for regressions, identify fault-tolerance pr...
The Ambient Kitchen is a high fidelity prototype for exploring the design of pervasive computing algorithms and applications for everyday environments. The environment integrates ...
Patrick Olivier, Guangyou Xu, Andrew Monk, Jesse H...
Multiprocessor SoCs are increasingly deployed in embedded systems with little or no security features built in. Code Injection attacks are one of the most commonly encountered sec...
Krutartha Patel, Sridevan Parameswaran, Seng Lin S...