We discuss the problem of assessing and aiding user performance in dynamic tasks that require rapid selection among multiple information sources. Motivated by research in human se...
Bradley C. Love, Matt Jones, Marc T. Tomlinson, Mi...
We propose a sequential randomized algorithm, which at each step concentrates on functions having both low risk and low variance with respect to the previous step prediction functi...
A mobile agent with the task to classify its sensor pattern has to cope with ambiguous information. Active recognition of three-dimensional objects involves the observer in a sear...
The temporal distance between events conveys information essential for numerous sequential tasks such as motor control and rhythm detection. While Hidden Markov Models tend to ign...
This work proposes a learning method for deep architectures that takes advantage of sequential data, in particular from the temporal coherence that naturally exists in unlabeled v...