195 citations · 458 across the 33 of their papers we have counts for
3 papers · 1 filter
Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders
Qi Le, Enmao Diao, Xinran Wang +3
Recommender Systems (RSs) have become increasingly important in many application domains, such as digital marketing. Conventional RSs often need to collect users' data, centralize…
A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation
Wenjing Yang, Ganghua Wang, Jie Ding +1
The goal of model compression is to reduce the size of a large neural network while retaining a comparable performance. As a result, computation and memory costs in resource-limite…
A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow
Mohammadreza Momenifar, Enmao Diao, Vahid Tarokh +1
Analyzing large-scale data from simulations of turbulent flows is memory intensive, requiring significant resources. This major challenge highlights the need for data compression t…