66 citations · 71 across the 13 of their papers we have counts for
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Convergence of a L2 regularized Policy Gradient Algorithm for the Multi Armed Bandit
Stefana Anita, Gabriel Turinici
Although Multi Armed Bandit (MAB) on one hand and the policy gradient approach on the other hand are among the most used frameworks of Reinforcement Learning, the theoretical prope…
Deep Conditional Measure Quantization
Gabriel Turinici
Quantization of a probability measure means representing it with a finite set of Dirac masses that approximates the input distribution well enough (in some metric space of probabil…
Huber-energy measure quantization
Gabriel Turinici
We describe a measure quantization procedure i.e., an algorithm which finds the best approximation of a target probability law (and more generally signed finite variation measure)…
Algorithms that get old : the case of generative deep neural networks
Gabriel Turinici
Generative deep neural networks used in machine learning, like the Variational Auto-Encoders (VAE), and Generative Adversarial Networks (GANs) produce new objects each time when as…