papers

Publications (14)

cs.IT2020

Optimal Linear Coding Schemes for the Secure Decentralized Pliable Index Coding Problem

Tang Liu, Daniela Tuninetti

We study the secure decentralized Pliable Index CODing (PICOD) problem with circular side information sets at the users. The security constraint forbids every user to decode more t…

cs.LG2021

Scaling Up Graph Neural Networks Via Graph Coarsening

Zengfeng Huang, Shengzhong Zhang, Chong Xi +2

Scalability of graph neural networks remains one of the major challenges in graph machine learning. Since the representation of a node is computed by recursively aggregating and tr…

cs.IT2019

Private Pliable Index Coding

Tang Liu, Daniela Tuninetti

The Pliable Index CODing (PICOD) problem is a variant of the Index Coding (IC) problem, where the desired messages by the users, who are equipped with message side information, is…

cs.IT2018

Tight Information Theoretic Converse Results for some Pliable Index Coding Problems

Tang Liu, Daniela Tuninetti

This paper studies the Pliable Index CODing problem (PICOD), which models content-type distribution networks. In the PICOD problem there are messages, users and each u…

cs.IT2014

The DoF of the Asymmetric MIMO Interference Channel with Square Direct Link Channel Matrices

Tang Liu, Daniela Tuninetti, Syed A. Jafar

This paper studies the sum Degrees of Freedom (DoF) of -user {\em asymmetric} MIMO Interference Channel (IC) with square direct link channel matrices, that is, the -th transm…

cs.LG2025

Enhancing the Cross-Size Generalization for Solving Vehicle Routing Problems via Continual Learning

Jingwen Li, Zhiguang Cao, Yaoxin Wu +1

Exploring machine learning techniques for addressing vehicle routing problems has attracted considerable research attention. To achieve decent and efficient solutions, existing dee…

cs.LG2025

Implicit vs Unfolded Graph Neural Networks

Yongyi Yang, Tang Liu, Yangkun Wang +2

It has been observed that message-passing graph neural networks (GNN) sometimes struggle to maintain a healthy balance between the efficient/scalable modeling of long-range depende…

cs.IT2020

Secure Decentralized Pliable Index Coding

Tang Liu, Daniela Tuninetti

This paper studies a variant of the Pliable Index CODing (PICOD) problem, i.e., an index coding problem where a user can be satisfied by decoding any message that is not in its sid…

cs.IT2015

On the DoF region of the two-user Interference Channel with an Instantaneous Relay

Tang Liu, Daniela Tuninetti, Sae-Young Chung

This paper studies the Degrees of Freedom (DoF) of the two-user multi-antenna Gaussian interference channel with an {\em instantaneous relay}, or relay without delay, where the rel…

cs.LG2021

Graph Neural Networks Inspired by Classical Iterative Algorithms

Yongyi Yang, Tang Liu, Yangkun Wang +6

Despite the recent success of graph neural networks (GNN), common architectures often exhibit significant limitations, including sensitivity to oversmoothing, long-range dependenci…

cs.IT2019

Decentralized Pliable Index Coding

Tang Liu, Daniela Tuninetti

This paper introduces the Pliable Index CODing (PICOD) problem: a variant of the Index Coding (IC) problem, where a central transmitter serves

cs.AI2026

RSMeM: Knowledge-Enhanced Memory Evolution for Remote Sensing Agents with Systematic Evaluation

Bingxian Wu, Yu Zhang, Zonghao Guo +9

Geoscience research requires complex analysis and domain expertise, with remote sensing (RS) observations as a key foundation. However, existing RS agents built on general-purpose…

cs.NI2011

Energy efficient prediction clustering algorithm for multilevel heterogeneous wireless sensor networks

Tang Liu, Jian Peng, Jin Yang +1

In designing wireless sensor networks, it is important to reduce energy dissipation and prolong network lifetime. In this paper, a new model with energy and monitored objects heter…

cs.IT2018

An Information Theoretic Converse for the "Consecutive Complete--" PICOD Problem

Tang Liu, Daniela Tuninetti

Pliable Index CODing (PICOD) is a variant of the Index Coding (IC) problem in which a user is satisfied whenever it can successfully decode any one message that is not in its side…