research
∙
10/20/2022
Pruning by Active Attention Manipulation
Filter pruning of a CNN is typically achieved by applying discrete masks...
share
research
∙
04/15/2022
End-to-End Sensitivity-Based Filter Pruning
In this paper, we present a novel sensitivity-based filter pruning algor...
research
∙
07/23/2021
Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition
We present a novel global compression framework for deep neural networks...
research
∙
06/25/2021
Closed-form Continuous-Depth Models
Continuous-depth neural models, where the derivative of the model's hidd...
research
∙
06/24/2021
Sparse Flows: Pruning Continuous-depth Models
Continuous deep learning architectures enable learning of flexible proba...
research
∙
04/06/2021
Low-Regret Active learning
We develop an online learning algorithm for identifying unlabeled data p...
research
∙
03/04/2021
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy
Neural network pruning is a popular technique used to reduce the inferen...
research
∙
02/19/2021
Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space
Learning competitive behaviors in multi-agent settings such as racing re...
research
∙
12/17/2019
Machine Learning-based Estimation of Forest Carbon Stocks to increase Transparency of Forest Preservation Efforts
An increasing amount of companies and cities plan to become CO2-neutral,...
research
∙
11/18/2019
Provable Filter Pruning for Efficient Neural Networks
We present a provable, sampling-based approach for generating compact Co...
research
∙
10/11/2019
SiPPing Neural Networks: Sensitivity-informed Provable Pruning of Neural Networks
We introduce a pruning algorithm that provably sparsifies the parameters...
research
∙
04/15/2018
