19 citations · 31 across the 5 of their papers we have counts for
5 papers · 1 filter
Deep Neural Networks for Encrypted Inference with TFHE
Andrei Stoian, Jordan Frery, Roman Bredehoft +3
Fully homomorphic encryption (FHE) is an encryption method that allows to perform computation on encrypted data, without decryption. FHE preserves the privacy of the users of onlin…
Regularization Shortcomings for Continual Learning
Timothée Lesort, Andrei Stoian, David Filliat
In most machine learning algorithms, training data is assumed to be independent and identically distributed (iid). When it is not the case, the algorithm's performances are challen…
Continual Learning for Robotics: Definition, Framework, Learning Strategies, Opportunities and Challenges
Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian +3
Continual learning (CL) is a particular machine learning paradigm where the data distribution and learning objective changes through time, or where all the training data and object…
Generative Models from the perspective of Continual Learning
Timothée Lesort, Hugo Caselles-Dupré, Michael Garcia-Ortiz +2
Which generative model is the most suitable for Continual Learning? This paper aims at evaluating and comparing generative models on disjoint sequential image generation tasks. We…
Marginal Replay vs Conditional Replay for Continual Learning
Timothée Lesort, Alexander Gepperth, Andrei Stoian +1
We present a new replay-based method of continual classification learning that we term "conditional replay" which generates samples and labels together by sampling from a distribut…