One of the nice properties of kernel classifiers such as SVMs is that they often produce sparse solutions. However, the decision functions of these classifiers cannot always be u...
We consider the problem of transmitting data at rate R over a state dependent channel p(ylx, s) with the state information available at the sender and at the same time conveying th...
The consistency of classification algorithm plays a central role in statistical learning theory. A consistent algorithm guarantees us that taking more samples essentially suffices...
We consider the problem of transmitting data at rate over a state-dependent channel with state information available at the sender and at the same time conveying the information ab...
An operational framework is developed for testing stationarity relatively to an observation scale, in both stochastic and deterministic contexts. The proposed method is based on a ...
Pierre Borgnat, Patrick Flandrin, Paul Honeine, C&...