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multiobjective-learning

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malena1906 / Pruning-Weights-with-Biobjective-Optimization-Keras

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Overparameterization and overfitting are common concerns when designing and training deep neural networks. Network pruning is an effective strategy used to reduce or limit the network complexity, but often suffers from time and computational intensive procedures to identify the most important connections and best performing hyperparameters. We s…

machine-learning sparsity ai tensorflow keras python3 image-classification automl l1-regularization network-compression unstructured-weight-pruning multiobjective-learning soft-pruning stochastic-multi-gradient dichotomic-serach dense-layers
  • Updated Sep 1, 2020
  • Python

levitation-opensource / ai-safety-gridworlds

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Extended, multi-agent and multi-objective (MaMoRL) environments based on DeepMind's AI Safety Gridworlds. This is a suite of reinforcement learning environments illustrating various safety properties of intelligent agents. It is made compatible with OpenAI's Gym/Gymnasium and Farama Foundation PettingZoo.

simulation-environment constraint-satisfaction-problem artificial-intelligence multi-agent gym simulation-framework rl multi-objective-optimization gridworld ai-safety multiobjective human-player gridworld-environment reinforcement-learning-environments marl sideeffects multiobjective-learning morl pettingzoo pluralism
  • Updated May 8, 2024
  • Python

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