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06/20/2022
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?
Collaborative multi-agent reinforcement learning (MARL) has been widely ...
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06/17/2022
Avoid Overfitting User Specific Information in Federated Keyword Spotting
Keyword spotting (KWS) aims to discriminate a specific wake-up word from...
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06/16/2022
Personalized Federated Learning via Variational Bayesian Inference
Federated learning faces huge challenges from model overfitting due to t...
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03/28/2022
Federated Learning with Position-Aware Neurons
Federated Learning (FL) fuses collaborative models from local nodes with...
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03/25/2022
Sparse Federated Learning with Hierarchical Personalization Models
Federated learning (FL) is widely used in the Internet of Things (IoT), ...
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03/23/2022
Mining Latent Relationships among Clients: Peer-to-peer Federated Learning with Adaptive Neighbor Matching
In federated learning (FL), clients may have diverse objectives, merging...
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11/30/2020
Unfolded Deep Neural Network (UDNN) for High Mobility Channel Estimation
High mobility channel estimation is crucial for beyond 5G (B5G) or 6G wi...
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08/03/2019
Risk Management via Anomaly Circumvent: Mnemonic Deep Learning for Midterm Stock Prediction
Midterm stock price prediction is crucial for value investments in the s...
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06/01/2019
Multi-dimensional Spectral Super-Resolution with Prior Knowledge via Frequency-Selective Vandermonde Decomposition and ADMM
This paper is concerned with estimation of multiple frequencies from inc...
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04/25/2019
Compressive Multidimensional Harmonic Retrieval with Prior Knowledge
This paper concerns the problem of estimating multidimensional (MD) freq...
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02/15/2019
