improvement

アルゴリズム:Algorithms

Protected: TRPO/PPO and DPG/DDPG, an improvement of the Policy Gradient method of reinforcement learning

TRPO/PPO and DPG/DDPG (Pendulum, Actor Critic, SequentialMemory, SequentialMemory, and SequentialMemory), which are improvements of Policy Gradient methods of reinforcement learning used for digital transformation, artificial intelligence, and machine learning tasks. Adam, keras-rl, TD error, Deep Deterministic Policy Gradient, Deterministic Policy Gradient, Advanced Actor Critic, A2C, A3C, Proximal Policy Optimization, Trust Region Policy Optimization, Python)
オンライン学習

Protected: Online prediction based on randomness

Randomness-based FPL(Follow the Perturbed Leader) Strategy and Gumbel Distribution for Improving Online Predictive Performance for Digital Transformation , Artificial Intelligence and Machine Learning Tasks
オンライン学習

Protected: Advanced online learning (3) Application to deep learning (mini-batch stochastic gradient descent, momentum method, accelerated gradient method)

Improving computational efficiency by applying mini-batch stochastic gradient descent, momentum, and accelerated gradient methods to deep learning for digital transformation , artificial intelligence , and machine learning tasks.
python

Protected: DNN for text and sequences with python and Keras (3) Advanced use of recurrent neural networks(GRU)

Analysis of sequence data by GRU with pyhton/keras used for digital transformation and artificial intelligence tasks and improvement by recurrent dropout and recurrent layer stacking
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