Papers Feature Compression
“Feature Compression” 태그가 달린 논문 96편 · 필터 해제
Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning
We consider the theoretical problem of designing an optimal adversarial attack on a decision system that maximally degrades the achievable performance of the system as measured by the mutual information between the degra…
Adversarial AttackBIG-bench Machine LearningFeature CompressionChromatic Learning for Sparse Datasets
Learning over sparse, high-dimensional data frequently necessitates the use of specialized methods such as the hashing trick. In this work, we design a highly scalable alternative approach that leverages the low degree o…
Feature CompressionJoint Device-Edge Inference over Wireless Links with Pruning
We propose a joint feature compression and transmission scheme for efficient inference at the wireless network edge. Our goal is to enable efficient and reliable inference at the edge server assuming limited computationa…
Feature CompressionGeneral Classificationimage-classificationImage Classification+1End-to-End Facial Deep Learning Feature Compression with Teacher-Student Enhancement
In this paper, we propose a novel end-to-end feature compression scheme by leveraging the representation and learning capability of deep neural networks, towards intelligent front-end equipped analysis with promising acc…
Feature CompressionVideo Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics
Video coding, which targets to compress and reconstruct the whole frame, and feature compression, which only preserves and transmits the most critical information, stand at two ends of the scale. That is, one is with com…
Feature CompressionVideo CompressionAn Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal
In this paper, we study a new problem arising from the emerging MPEG standardization effort Video Coding for Machine (VCM), which aims to bridge the gap between visual feature compression and classical video coding. VCM …
Action RecognitionFeature CompressionSSIMBottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems
The emergence of various intelligent mobile applications demands the deployment of powerful deep learning models at resource-constrained mobile devices. The device-edge co-inference framework provides a promising solutio…
DecoderEdge-computingFeature CompressionTrust but Verify: An Information-Theoretic Explanation for the Adversarial Fragility of Machine Learning Systems, and a General Defense against Adversarial Attacks
Deep-learning based classification algorithms have been shown to be susceptible to adversarial attacks: minor changes to the input of classifiers can dramatically change their outputs, while being imperceptible to humans…
Feature CompressionCategorical Feature Compression via Submodular Optimization
In the era of big data, learning from categorical features with very large vocabularies (e.g., 28 million for the Criteo click prediction dataset) has become a practical challenge for machine learning researchers and pra…
Feature CompressionComparing of Term Clustering Frameworks for Modular Ontology Learning
This paper aims to use term clustering to build a modular ontology according to core ontology from domain-specific text. The acquisition of semantic knowledge focuses on noun phrase appearing with the same syntactic role…
ClusteringDimensionality ReductionFeature Compressionfeature selection+1Intermediate Deep Feature Compression: the Next Battlefield of Intelligent Sensing
The recent advances of hardware technology have made the intelligent analysis equipped at the front-end with deep learning more prevailing and practical. To better enable the intelligent sensing at the front-end, instead…
Data CompressionDeep LearningFeature CompressionNear-Lossless Deep Feature Compression for Collaborative Intelligence
Collaborative intelligence is a new paradigm for efficient deployment of deep neural networks across the mobile-cloud infrastructure. By dividing the network between the mobile and the cloud, it is possible to distribute…
Feature CompressionContext-aware Deep Feature Compression for High-speed Visual Tracking
We propose a new context-aware correlation filter based tracking framework to achieve both high computational speed and state-of-the-art performance among real-time trackers. The major contribution to the high computatio…
DenoisingFeature CompressionVisual Object TrackingVisual Tracking+1Deep feature compression for collaborative object detection
Recent studies have shown that the efficiency of deep neural networks in mobile applications can be significantly improved by distributing the computational workload between the mobile device and the cloud. This paradigm…
Feature CompressionObjectobject-detectionObject DetectionPixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks
We propose a novel video object segmentation algorithm based on pixel-level matching using Convolutional Neural Networks (CNN). Our network aims to distinguish the target area from the background on the basis of the pixe…
Feature CompressionObjectSemantic SegmentationSemi-Supervised Video Object Segmentation+3Compact Representation for Image Classification: To Choose or to Compress?
In large scale image classification, features such as Fisher vector or VLAD have achieved state-of-the-art results. However, the combination of large number of examples and high dimensional vectors necessitates dimension…
ClassificationCPUDimensionality ReductionFeature Compression+5