67 citations · 297 across the 34 of their papers we have counts for
4 papers · 1 filter
Generative Adversarial Learning via Kernel Density Discrimination
Abdelhak Lemkhenter, Adam Bielski, Alp Eren Sari +1
We introduce Kernel Density Discrimination GAN (KDD GAN), a novel method for generative adversarial learning. KDD GAN formulates the training as a likelihood ratio optimization pro…
KOALA: A Kalman Optimization Algorithm with Loss Adaptivity
Aram Davtyan, Sepehr Sameni, Llukman Cerkezi +3
Optimization is often cast as a deterministic problem, where the solution is found through some iterative procedure such as gradient descent. However, when training neural networks…
A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
We propose a novel GAN training scheme that can handle any level of labeling in a unified manner. Our scheme introduces a form of artificial labeling that can incorporate manually…
Boosting Generalization in Bio-Signal Classification by Learning the Phase-Amplitude Coupling
Abdelhak Lemkhenter, Paolo Favaro
Various hand-crafted features representations of bio-signals rely primarily on the amplitude or power of the signal in specific frequency bands. The phase component is often discar…