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Found 4 papers, 0 papers with code
Learning Compact Neural Networks with Deep Overparameterised Multitask Learning
Compact neural network offers many benefits for real-world applications.
Deep Multitask Learning with Progressive Parameter Sharing
A scheduling mechanism following the concept of curriculum learning is also designed to progressively change the sharing strategy to increase the level of sharing during the learning process.
An Entropy Regularization Free Mechanism for Policy-based Reinforcement Learning
We find valued-based reinforcement learning methods with {\epsilon}-greedy mechanism are capable of enjoying three characteristics, Closed-form Diversity, Objective-invariant Exploration and Adaptive Trade-off, which help value-based methods avoid the policy collapse problem.
CASA: Bridging the Gap between Policy Improvement and Policy Evaluation with Conflict Averse Policy Iteration
We study the problem of model-free reinforcement learning, which is often solved following the principle of Generalized Policy Iteration (GPI).
