Search Results for author: Shirin Saeedi Bidokhti

Found 10 papers, 2 papers with code

Decentralized Learning Strategies for Estimation Error Minimization with Graph Neural Networks

no code implementations4 Apr 2024 Xingran Chen, Navid Naderializadeh, Alejandro Ribeiro, Shirin Saeedi Bidokhti

Our goal is to minimize time-average estimation error and/or age of information with decentralized scalable sampling and transmission policies, considering both oblivious (where decision-making is independent of the physical processes) and non-oblivious policies (where decision-making depends on physical processes).

Decision Making Multi-agent Reinforcement Learning

Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding

no code implementations12 Mar 2024 Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti

On general vector sources, LTC improves upon standard neural compressors in one-shot coding performance.

Quantization

Text + Sketch: Image Compression at Ultra Low Rates

1 code implementation4 Jul 2023 Eric Lei, Yiğit Berkay Uslu, Hamed Hassani, Shirin Saeedi Bidokhti

Recent advances in text-to-image generative models provide the ability to generate high-quality images from short text descriptions.

Image Compression

On a Relation Between the Rate-Distortion Function and Optimal Transport

no code implementations1 Jul 2023 Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti

We discuss a relationship between rate-distortion and optimal transport (OT) theory, even though they seem to be unrelated at first glance.

Quantization Relation

Federated Neural Compression Under Heterogeneous Data

no code implementations25 May 2023 Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti

We discuss a federated learned compression problem, where the goal is to learn a compressor from real-world data which is scattered across clients and may be statistically heterogeneous, yet share a common underlying representation.

Personalized Federated Learning

Neural Estimation of the Rate-Distortion Function With Applications to Operational Source Coding

1 code implementation4 Apr 2022 Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti

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.

Data Compression

Robust Graph Neural Networks via Probabilistic Lipschitz Constraints

no code implementations14 Dec 2021 Raghu Arghal, Eric Lei, Shirin Saeedi Bidokhti

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

no code implementations13 Oct 2021 Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti

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

no code implementations17 Feb 2021 Xingran Chen, Renpu Liu, Shaochong Wang, Shirin Saeedi Bidokhti

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

no code implementations7 Jul 2020 Xingran Chen, Xinyu Liao, Shirin Saeedi Bidokhti

It is shown that non-oblivious policies offer a multiplicative gain close to $3$ compared to oblivious policies.

Decision Making Scheduling

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