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05/25/2023
Towards Automatic Neural Architecture Search within General Super-Networks
Existing neural architecture search (NAS) methods typically rely on pre-...
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03/13/2023
OTOV2: Automatic, Generic, User-Friendly
The existing model compression methods via structured pruning typically ...
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09/09/2022
Sparsity-guided Network Design for Frame Interpolation
DNN-based frame interpolation, which generates intermediate frames from ...
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03/27/2022
RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolution
Space-time video super-resolution (STVSR) is the task of interpolating v...
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03/02/2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
When training deep neural networks for classification tasks, an intrigui...
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07/15/2021
Only Train Once: A One-Shot Neural Network Training And Pruning Framework
Structured pruning is a commonly used technique in deploying deep neural...
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05/06/2021
A Geometric Analysis of Neural Collapse with Unconstrained Features
We provide the first global optimization landscape analysis of Neural Co...
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03/18/2021
CDFI: Compression-Driven Network Design for Frame Interpolation
DNN-based frame interpolation–that generates the intermediate frames giv...
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11/10/2020
Neural Network Compression Via Sparse Optimization
The compression of deep neural networks (DNNs) to reduce inference cost ...
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10/20/2020
Early Detection of Sepsis using Ensemblers
This paper describes a methodology to detect sepsis ahead of time by ana...
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04/07/2020
