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Found 6 papers, 1 papers with code
Heterogeneous Multi-Agent Reinforcement Learning via Mirror Descent Policy Optimization
This paper presents an extension of the Mirror Descent method to overcome challenges in cooperative Multi-Agent Reinforcement Learning (MARL) settings, where agents have varying abilities and individual policies.
Multidimensional Data Analysis Based on Block Convolutional Tensor Decomposition
Besides tensor decompositions like Tucker and CP, Tensor SVD (t-SVD) which is based on the t-product of tensors is another extension of SVD to tensors that recently developed and has found numerous applications in analyzing high dimensional data.
Local and Global Structure Preservation Based Spectral Clustering
SC aims to cluster data by considering the preservation of the local neighborhood structure on the manifold data.
An adaptive synchronization approach for weights of deep reinforcement learning
To test this method, we adjusted the DQN and rainbow methods with the proposed adaptive synchronization method.
End-to-End CNN+LSTM Deep Learning Approach for Bearing Fault Diagnosis
Fault diagnostics and prognostics are important topics both in practice and research.
A novel extension of Generalized Low-Rank Approximation of Matrices based on multiple-pairs of transformations
Due to these issues, in recent years some methods like Generalized low-rank approximation of matrices (GLRAM) and Multilinear PCA (MPCA) are proposed which deal with the data in their own format.
