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06/22/2023
Communication-Efficient Federated Learning through Importance Sampling
The high communication cost of sending model updates from the clients to...
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06/08/2023
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation
We study the mean estimation problem under communication and local diffe...
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03/20/2023
Sandwiched Video Compression: Efficiently Extending the Reach of Standard Codecs with Neural Wrappers
We propose sandwiched video compression – a video compression system tha...
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10/14/2022
Upper bounds on the Rate of Uniformly-Random Codes for the Deletion Channel
We consider the maximum coding rate achievable by uniformly-random codes...
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09/30/2022
Sparse Random Networks for Communication-Efficient Federated Learning
One main challenge in federated learning is the large communication cost...
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02/07/2022
Learning under Storage and Privacy Constraints
Storage-efficient privacy-guaranteed learning is crucial due to enormous...
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11/17/2021
LVAC: Learned Volumetric Attribute Compression for Point Clouds using Coordinate Based Networks
We consider the attributes of a point cloud as samples of a vector-value...
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05/07/2021
Neural 3D Scene Compression via Model Compression
Rendering 3D scenes requires access to arbitrary viewpoints from the sce...
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02/16/2021
Successive Pruning for Model Compression via Rate Distortion Theory
Neural network (NN) compression has become essential to enable deploying...
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02/15/2021
Neural Network Compression for Noisy Storage Devices
Compression and efficient storage of neural network (NN) parameters is c...
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11/20/2020
Noisy Neural Network Compression for Analog Storage Devices
Efficient compression and storage of neural network (NN) parameters is c...
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05/21/2020