Data Compression with Bayesian Attention Networks
The lossless data compression algorithm based on Bayesian Attention Networks is derived from first principles.
Code (0)
등록된 구현이 없습니다.
Tasks
Data CompressionSimilar Papers 제목 키워드 기반
Bayesian Attention Networks for Data Compression
The lossless data compression algorithm based on Bayesian Attention Networks is derived from first principles. Bayesian Attention Networks are defined by introducing an attention factor per a training sample loss as a fu…
Data CompressionPredictionPredicting Eye Fixations Under Distortion Using Bayesian Observers
Visual attention is very an essential factor that affects how human perceives visual signals. This report investigates how distortions in an image could distract human's visual attention using Bayesian visual search mode…
BlockingEfficient Model Compression for Bayesian Neural Networks
Model Compression has drawn much attention within the deep learning community recently. Compressing a dense neural network offers many advantages including lower computation cost, deployability to devices of limited stor…
Deep Learningfeature selectionmodelModel Compression+1On Compression Principle and Bayesian Optimization for Neural Networks
Finding methods for making generalizable predictions is a fundamental problem of machine learning. By looking into similarities between the prediction problem for unknown data and the lossless compression we have found a…
Bayesian OptimizationDimensionality ReductionEnhanced Bayesian Compression via Deep Reinforcement Learning
In this paper, we propose an Enhanced Bayesian Compression method to flexibly compress the deep networks via reinforcement learning. Unlike the existing Bayesian compression method which cannot explicitly enforce quantiz…
Deep Reinforcement LearningQuantizationreinforcement-learningReinforcement Learning+1