It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
We study a subclass of POMDPs, called quasi-deterministic POMDPs (QDET-POMDPs), characterized by deterministic actions and stochastic observations. While this framework does not mo...
Trust dynamics can be modelled in relation to experiences. Both cognitive and neural models for trust dynamics in relation to experiences are available, but were not yet related or...
In pattern recognition systems, data fusion is an important issue and evidence theory is one such method that has been successful. Many researchers have proposed different rules fo...
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...
In contrast to traditional machine learning algorithms, where all data are available in batch mode, the new paradigm of streaming data poses additional difficulties, since data sam...
In this paper, we introduce a novel incremental subspace based object tracking algorithm. The two major contributions of our work are the Robust PCA based occlusion handling scheme...