Spiking Neural Networks (SNNs) are biologically inspired alternatives to...
Recent successes of massively overparameterized models have inspired a n...
We focus on the continual learning problem where the tasks arrive
sequen...
We prove rigorous results on the double descent phenomenon in random fea...
We consider estimation under model misspecification where there is a mod...
We consider a linear minimum mean squared error (LMMSE) estimation frame...
Active Inference (ActInf) is an emerging theory that explains perception...
Distributed learning provides an attractive framework for scaling the
le...
Distributed learning facilitates the scaling-up of data processing by
di...
Random non-linear Fourier features have recently shown remarkable perfor...
We consider a sensing application where the sensor nodes are wirelessly
...