SOTAVerified

Feature Compression

Compress data for machine interpretability to perform downstream tasks, rather than for human perception.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 81–90 of 96 papers

TitleStatusHype
Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning—0
Chromatic Learning for Sparse Datasets—0
Joint Device-Edge Inference over Wireless Links with Pruning—0
End-to-End Facial Deep Learning Feature Compression with Teacher-Student Enhancement—0
Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics—0
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal—0
BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference SystemsCode0
Trust but Verify: An Information-Theoretic Explanation for the Adversarial Fragility of Machine Learning Systems, and a General Defense against Adversarial Attacks—0
Categorical Feature Compression via Submodular Optimization—0
Comparing of Term Clustering Frameworks for Modular Ontology Learning—0
Show:102550
← PrevPage 9 of 10Next →

No leaderboard results yet.