This paper proposes a technique for identifying program properties that indicate errors. The technique generates machine learning models of program properties known to result from...
As agent systems are solving more and more complex tasks in increasingly challenging domains, the systems themselves are becoming more complex too, often compromising their adapti...
In this paper, we present a Deformable Action Template
(DAT) model that is learnable from cluttered real-world
videos with weak supervisions. In our generative model,
an action ...
Dynamic analysis techniques have been extensively adopted to discover causes of observed failures. In particular, anomaly detection techniques can infer behavioral models from obs...
We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a n...