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08/24/2023
Code Llama: Open Foundation Models for Code
We release Code Llama, a family of large language models for code based ...
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09/29/2022
Does Zero-Shot Reinforcement Learning Exist?
A zero-shot RL agent is an agent that can solve any RL task in a given e...
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08/25/2022
Decoding speech from non-invasive brain recordings
Decoding language from brain activity is a long-awaited goal in both hea...
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10/08/2020
Black-Box Optimization Revisited: Improving Algorithm Selection Wizards through Massive Benchmarking
Existing studies in black-box optimization suffer from low generalizabil...
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10/08/2020
Population Based Training for Data Augmentation and Regularization in Speech Recognition
Varying data augmentation policies and regularization over the course of...
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09/28/2020
EvolGAN: Evolutionary Generative Adversarial Networks
We propose to use a quality estimator and evolutionary methods to search...
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04/29/2020
Versatile Black-Box Optimization
Choosing automatically the right algorithm using problem descriptors is ...
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04/24/2020
Variance Reduction for Better Sampling in Continuous Domains
Design of experiments, random search, initialization of population-based...
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04/24/2020
Proving μ>1
Choosing the right selection rate is a long standing issue in evolutiona...
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01/27/2020
Polygames: Improved Zero Learning
Since DeepMind's AlphaZero, Zero learning quickly became the state-of-th...
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06/17/2019
Inspirational Adversarial Image Generation
The task of image generation started to receive some attention from arti...
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07/08/2015
Robust Sparse Blind Source Separation
Blind Source Separation is a widely used technique to analyze multichann...
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12/09/2014
Sparsity and adaptivity for the blind separation of partially correlated sources
Blind source separation (BSS) is a very popular technique to analyze mul...
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07/29/2014
NMF with Sparse Regularizations in Transformed Domains
Non-negative blind source separation (non-negative BSS), which is also r...
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08/26/2013