activity
20062020
most citedSecure Nested Codes for Type II Wiretap Channels

79 citations · 382 across the 31 of their papers we have counts for

collaborators

31 papers

cs.IT2020★ 1 cited

Self-Secure Capacity-Achieving Feedback Schemes of Gaussian Multiple-Access Wiretap Channels with Degraded Message Sets

Bin Dai, Chong Li, Yingbin Liang +2

The Schalkwijk-Kailath (SK) scheme, which achieves the capacity of the point-to-point white Gaussian channel with feedback, is secure by itself and also achieves the secrecy capaci…

cs.IT2018★ 2 cited

Parallel Gaussian Channels Corrupted by Independent States With a State-Cognitive Helper

Michael Dikshtein, Ruchen Duan, Yingbin Liang +1

We consider a state-dependent parallel Gaussian channel with independent states and a common cognitive helper, in which two transmitters wish to send independent information to the…

cs.IT2018

State-Dependent Interference Channel with Correlated States

Yunhao Sun, Ruchen Duan, Yingbin Liang +1

This paper investigates the Gaussian state-dependent interference channel (IC) and Z-IC, in which two receivers are corrupted respectively by two different but correlated states th…

cs.IT2016★ 9 cited

Degraded Broadcast Channel with Secrecy Outside a Bounded Range

Shaofeng Zou, Yingbin Liang, Lifeng Lai +2

The -receiver degraded broadcast channel with secrecy outside a bounded range is studied, in which a transmitter sends messages to receivers, and the channel quality gra…

cs.IT2016★ 7 cited

Estimation of KL Divergence: Optimal Minimax Rate

Yuheng Bu, Shaofeng Zou, Yingbin Liang +1

The problem of estimating the Kullback-Leibler divergence between two unknown distributions and is studied, under the assumption that the alphabet size of the…

stat.ML2016★ 19 cited

Nonparametric Detection of Geometric Structures over Networks

Shaofeng Zou, Yingbin Liang, H. Vincent Poor

Nonparametric detection of existence of an anomalous structure over a network is investigated. Nodes corresponding to the anomalous structure (if one exists) receive samples genera…