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Found 5 papers, 1 papers with code
Neural Estimation of the Rate-Distortion Function With Applications to Operational Source Coding
Motivated by the empirical success of deep neural network (DNN) compressors on large, real-world data, we investigate methods to estimate the rate-distortion function on such data, which would allow comparison of DNN compressors with optimality.
Robust Graph Neural Networks via Probabilistic Lipschitz Constraints
This allows for the use of the same computationally efficient algorithm on sampled constraints, which provides PAC-style guarantees on the stability of the GNN using results in scenario optimization.
Out-of-Distribution Robustness in Deep Learning Compression
In recent years, deep neural network (DNN) compression systems have proved to be highly effective for designing source codes for many natural sources.
Timely Broadcasting in Erasure Networks: Age-Rate Tradeoffs
The interplay between timeliness and rate efficiency is investigated in packet erasure broadcast channels with feedback.
Information Theory Social and Information Networks Systems and Control Systems and Control Information Theory
Real-time Sampling and Estimation on Random Access Channels: Age of Information and Beyond
It is shown that non-oblivious policies offer a multiplicative gain close to $3$ compared to oblivious policies.
