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07/01/2023
S-Omninet: Structured Data Enhanced Universal Multimodal Learning Architecture
Multimodal multitask learning has attracted an increasing interest in re...
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06/04/2023
Riemannian Low-Rank Model Compression for Federated Learning with Over-the-Air Aggregation
Low-rank model compression is a widely used technique for reducing the c...
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08/17/2021
Aggregation Delayed Federated Learning
Federated learning is a distributed machine learning paradigm where mult...
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04/21/2021
Efficient Sparse Coding using Hierarchical Riemannian Pursuit
Sparse coding is a class of unsupervised methods for learning a sparse r...
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03/02/2021
Online Orthogonal Dictionary Learning Based on Frank-Wolfe Method
Dictionary learning is a widely used unsupervised learning method in sig...
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06/13/2020
Line-of-Sight MIMO for High Capacity Millimeter Wave Backhaul in FDD Systems
Wireless backhaul is considered to be the key part of the future wireles...
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04/26/2020
Blind Data Detection in Massive MIMO via ℓ_3-norm Maximization over the Stiefel Manifold
Massive MIMO has been regarded as a key enabling technique for 5G and be...
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02/24/2020
Complete Dictionary Learning via ℓ_p-norm Maximization
Dictionary learning is a classic representation learning method that has...
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08/12/2019
Mixture-based Multiple Imputation Models for Clinical Data with a Temporal Dimension
The problem of missing values in multivariable time series is a key chal...
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08/12/2019