output
20082025
most citedClick-Through Rate Prediction with Multi-Modal Hypergraphs

48 citations

30 papers

cond-mat.mtrl-sci2025★ 1 cited

Resonant states and nuclear dynamics in solid-state systems: the case of silicon-hydrogen bond dissociation

Woncheol Lee, Mark E. Turiansky, Dominic Waldhör +3

Bond breaking in the presence of highly energetic carriers is central to many important phenomena in physics and chemistry, including radiation damage, hot-carrier degradation, act…

cs.IT2024★ 9 cited

Learned Pulse Shaping Design for PAPR Reduction in DFT-s-OFDM

Fabrizio Carpi, Soheil Rostami, Joonyoung Cho +3

High peak-to-average power ratio (PAPR) is one of the main factors limiting cell coverage for cellular systems, especially in the uplink direction. Discrete Fourier transform sprea…

cs.IT2023★ 41 cited

Joint Phase-Time Arrays: A Paradigm for Frequency-Dependent Analog Beamforming in 6G

Vishnu V. Ratnam, Jianhua Mo, Ahmad AlAmmouri +4

Hybrid beamforming is an attractive solution to build cost-effective and energy-efficient transceivers for millimeter-wave and terahertz systems. However, conventional hybrid beamf…

cs.NI2023

Towards Intelligent Network Management: Leveraging AI for Network Service Detection

Khuong N. Nguyen, Abhishek Sehgal, Yuming Zhu +5

As the complexity and scale of modern computer networks continue to increase, there has emerged an urgent need for precise traffic analysis, which plays a pivotal role in cutting-e…

cs.IT2023★ 35 cited

Optimal preprocessing of WiFi CSI for sensing applications

Vishnu V. Ratnam, Hao Chen, Hao Hsuan Chang +3

Due to its ubiquitous and contact-free nature, the use of WiFi infrastructure for performing sensing tasks has tremendous potential. However, the channel state information (CSI) me…

cs.LG2022★ 4 cited

FairMILE: Towards an Efficient Framework for Fair Graph Representation Learning

Yuntian He, Saket Gurukar, Srinivasan Parthasarathy

Graph representation learning models have demonstrated great capability in many real-world applications. Nevertheless, prior research indicates that these models can learn biased r…