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Yameng Chang

dblp:207/7570 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Coding theory · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › source coding › multiterminal source coding
distributed source coding
0.412020
Generalized Gaussian Multiterminal Source Coding: The Symmetric Case · IEEE Trans. Inf. Theory 2020
Coding theory › source coding › multiterminal source coding
gaussian multiterminal source coding
0.412020
Generalized Gaussian Multiterminal Source Coding: The Symmetric Case · IEEE Trans. Inf. Theory 2020
Coding theory › source coding
multiterminal source coding
0.412020
Generalized Gaussian Multiterminal Source Coding: The Symmetric Case · IEEE Trans. Inf. Theory 2020
Coding theory › source coding
rate-distortion theory
0.412020
Generalized Gaussian Multiterminal Source Coding: The Symmetric Case · IEEE Trans. Inf. Theory 2020

Methods — techniques the papers use, named apart from their topics

operator inequality · 0.4matrix analysis · 0.4
YearPublicationVenuePosition
2020 Generalized Gaussian Multiterminal Source Coding: The Symmetric Case
abstract
Consider a generalized multiterminal source coding system, where (mℓ) encoders, each observing a distinct size-m subset of I (ℓ ≥ 2) zero-mean unit-variance exchangeable Gaussian sources with correlation coefficient p, compress their observations in such a way that a joint decoder can reconstruct the sources within a prescribed mean squared error distortion based on the compressed data. The optimal rate-distortion performance of this system was previously known only for the two extreme cases m = ℓ (the centralized case) and m = 1 (the distributed case), and except when ρ = 0, the centralized system can achieve strictly lower compression rates than the distributed system under all non-trivial distortion constraints. Somewhat surprisingly, it is established in the present paper that the optimal rate-distortion performance of the afore-described generalized multiterminal source coding system with m ≥ 2 coincides with that of the centralized system for all distortions when ρ ≤ 0 and for distortions below an explicit positive threshold (depending on m) when ρ > 0. Moreover, when ρ > 0, the minimum achievable rate of generalized multiterminal source coding subject to an arbitrary positive distortion constraint d is shown to be within a finite gap (depending on m and d) from its centralized counterpart in the large I limit except for possibly the critical distortion d = 1 - ρ.
Jun Chen 0005, Yameng Chang, Jia Wang 0004, Yizhong Wang
IEEE Trans. Inf. Theory3
2018 Symmetric Generalized Gaussian Multiterminal Source Coding
abstract
Consider a generalized multiterminal source coding system, where (ℓ : m) encoders, each observing a distinct size-m subset of ℓ(ℓ ≥ 2) zero-mean unit-variance symmetrically correlated Gaussian sources with correlation coefficient ρ, compress their observations in such a way that a joint decoder can reconstruct the sources within a prescribed mean squared error distortion based on the compressed data. The optimal rate-distortion performance of this system was previously known only for the two extreme cases m = ℓ (the centralized case) and m = 1 (the distributed case), and except when ρ = 0, the centralized system can achieve strictly lower compression rates than the distributed system under all non-trivial distortion constraints. Somewhat surprisingly, it is established in the present paper that the optimal rate-distortion performance of the afore-described generalized multiterminal source coding system with m ≥ 2 coincides with that of the centralized system for all distortions when ρ ≤ 0 and for distortions below an explicit positive threshold (depending on m) when ρ > 0.
Jun Chen 0005, Yameng Chang, Jia Wang 0004, Yizhong Wang
ISIT3