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06/08/2023
Robust Quickest Change Detection for Unnormalized Models
Detecting an abrupt and persistent change in the underlying distribution...
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02/11/2023
Pruning Deep Neural Networks from a Sparsity Perspective
In recent years, deep network pruning has attracted significant attentio...
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02/01/2023
Quickest Change Detection for Unnormalized Statistical Models
Classical quickest change detection algorithms require modeling pre-chan...
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12/17/2022
Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders
Recommender Systems (RSs) have become increasingly important in many app...
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06/11/2022
A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation
The goal of model compression is to reduce the size of a large neural ne...
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01/10/2022
A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow
Analyzing large-scale data from simulations of turbulent flows is memory...
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12/07/2021
Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning Models
We use a data-driven approach to model a three-dimensional turbulent flo...
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10/26/2021
Privacy-Preserving Multi-Target Multi-Domain Recommender Systems with Assisted AutoEncoders
A long-standing challenge in Recommender Systems (RCs) is the data spars...
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06/02/2021
SemiFL: Communication Efficient Semi-Supervised Federated Learning with Unlabeled Clients
Federated Learning allows training machine learning models by using the ...
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06/02/2021
Gradient Assisted Learning
In distributed settings, collaborations between different entities, such...
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12/24/2020
On Statistical Efficiency in Learning
A central issue of many statistical learning problems is to select an ap...
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10/03/2020
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
Federated Learning (FL) is a method of training machine learning models ...
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02/07/2020
Multimodal Controller for Generative Models
Class-conditional generative models are crucial tools for data generatio...
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10/23/2019
Deep Clustering of Compressed Variational Embeddings
Motivated by the ever-increasing demands for limited communication bandw...
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10/20/2019
Speech Emotion Recognition with Dual-Sequence LSTM Architecture
Speech Emotion Recognition (SER) has emerged as a critical component of ...
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08/21/2019
Restricted Recurrent Neural Networks
Recurrent Neural Network (RNN) and its variations such as Long Short-Ter...
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03/23/2019