482 citations · 1.4k across the 36 of their papers we have counts for
3 papers · 1 filter
Learning to Prune Deep Neural Networks via Reinforcement Learning
Manas Gupta, Siddharth Aravindan, Aleksandra Kalisz +2
This paper proposes PuRL - a deep reinforcement learning (RL) based algorithm for pruning neural networks. Unlike current RL based model compression approaches where feedback is gi…
Empirical Analysis of Overfitting and Mode Drop in GAN Training
Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler +2
We examine two key questions in GAN training, namely overfitting and mode drop, from an empirical perspective. We show that when stochasticity is removed from the training procedur…
Classify and Generate: Using Classification Latent Space Representations for Image Generations
Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici +3
Utilization of classification latent space information for downstream reconstruction and generation is an intriguing and a relatively unexplored area. In general, discriminative re…