3 citations · 8 across the 11 of their papers we have counts for
3 papers · 1 filter
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models
Nikolaos Dimitriadis, Pascal Frossard, François Fleuret
In Multi-Task Learning (MTL), tasks may compete and limit the performance achieved on each other, rather than guiding the optimization to a solution, superior to all its single-tas…
U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search
Ahmet Caner Yüzügüler, Nikolaos Dimitriadis, Pascal Frossard
Optimizing resource utilization in target platforms is key to achieving high performance during DNN inference. While optimizations have been proposed for inference latency, memory…
The Theoretical Expressiveness of Maxpooling
Kyle Matoba, Nikolaos Dimitriadis, François Fleuret
Over the decade since deep neural networks became state of the art image classifiers there has been a tendency towards less use of max pooling: the function that takes the largest…