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 21–30 of 96 papers

TitleStatusHype
An Efficient Large Recommendation Model: Towards a Resource-Optimal Scaling Law—0
Trust but Verify: An Information-Theoretic Explanation for the Adversarial Fragility of Machine Learning Systems, and a General Defense against Adversarial Attacks—0
Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning—0
Distilling Channels for Efficient Deep Tracking—0
Distributed and Rate-Adaptive Feature Compression—0
DMOFC: Discrimination Metric-Optimized Feature Compression—0
Deep Reinforcement Learning for Wireless Resource Allocation Using Buffer State Information—0
Dynamic Semantic Compression for CNN Inference in Multi-access Edge Computing: A Graph Reinforcement Learning-based Autoencoder—0
Dynamic Submodular Maximization—0
Joint Device-Edge Inference over Wireless Links with Pruning—0
Show:102550
← PrevPage 3 of 10Next →

No leaderboard results yet.