Andrei Kucharavy | DeepAI

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∙ 05/20/2023

Evolutionary Algorithms in the Light of SGD: Limit Equivalence, Minima Flatness, and Transfer Learning

Whenever applicable, the Stochastic Gradient Descent (SGD) has shown its...

0 Andrei Kucharavy, et al. ∙

∙ 04/20/2023

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Modern machine learning (ML) models are capable of impressive performanc...

0 Andrei Kucharavy, et al. ∙

∙ 04/18/2023

Stochastic Parrots Looking for Stochastic Parrots: LLMs are Easy to Fine-Tune and Hard to Detect with other LLMs

The self-attention revolution allowed generative language models to scal...

0 Da Silva Gameiro Henrique, et al. ∙

∙ 03/21/2023

Fundamentals of Generative Large Language Models and Perspectives in Cyber-Defense

Generative Language Models gained significant attention in late 2022 / e...

0 Andrei Kucharavy, et al. ∙

∙ 06/01/2022

Needle In A Haystack, Fast: Benchmarking Image Perceptual Similarity Metrics At Scale

The advent of the internet, followed shortly by the social media made it...

0 Cyril Vallez, et al. ∙

∙ 08/26/2021

Can the Transformer Be Used as a Drop-in Replacement for RNNs in Text-Generating GANs?

In this paper we address the problem of fine-tuned text generation with ...

0 Kevin Blin, et al. ∙

∙ 05/22/2020

Host-Pathongen Co-evolution Inspired Algorithm Enables Robust GAN Training

Generative adversarial networks (GANs) are pairs of artificial neural ne...

0 Andrei Kucharavy, et al. ∙

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