Shashank Jere

According to our database, Shashank Jere authored at least 18 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Learning at the Speed of Wireless: Online Real-Time Learning for AI-Enabled MIMO in NextG.

Jiarui Xu, Shashank Jere, Yifei Song, Yi-Hung Kao, Lizhong Zheng, Lingjia Liu

CoRR, 2024

2023

Theoretical Foundation and Design Guideline for Reservoir Computing-Based MIMO-OFDM Symbol Detection.

Shashank Jere, Ramin Safavinejad, Lingjia Liu

IEEE Trans. Commun., September, 2023

Performance Analysis and Optimization for Layer-Based Scalable Video Caching in 6G Networks.

Junchao Ma, Lingjia Liu, Bodong Shang, Shashank Jere, Pingzhi Fan

IEEE/ACM Trans. Netw., August, 2023

Channel Equalization Through Reservoir Computing: A Theoretical Perspective.

Shashank Jere, Ramin Safavinejad, Lizhong Zheng, Lingjia Liu

IEEE Wirel. Commun. Lett., May, 2023

Distributed Learning Meets 6G: A Communication and Computing Perspective.

Shashank Jere, Yifei Song, Yang Yi, Lingjia Liu

IEEE Wirel. Commun., February, 2023

Universal Approximation of Linear Time-Invariant (LTI) Systems through RNNs: Power of Randomness in Reservoir Computing.

Shashank Jere, Lizhong Zheng, Karim Said, Lingjia Liu

CoRR, 2023

Towards Explainable Machine Learning: The Effectiveness of Reservoir Computing in Wireless Receive Processing.

Shashank Jere, Karim Said, Lizhong Zheng, Lingjia Liu

Proceedings of the IEEE Military Communications Conference, 2023

2022

Error bound characterization for reservoir computing-based OFDM symbol detection.

Shashank Jere, Hussein Metwaly Saad, Lingjia Liu

Proceedings of the IEEE International Conference on Communications, 2022

Anonymous Jamming Detection in 5G with Bayesian Network Model Based Inference Analysis.

Ying Wang, Shashank Jere, Soumya Banerjee, Lingjia Liu, Sachin Shetty, Shehadi Dayekh

Proceedings of the 23rd IEEE International Conference on High Performance Switching and Routing, 2022

2021

RCNet: Incorporating Structural Information Into Deep RNN for Online MIMO-OFDM Symbol Detection With Limited Training.

Zhou Zhou, Lingjia Liu, Shashank Jere, Jianzhong Zhang, Yang Yi

IEEE Trans. Wirel. Commun., 2021

Federated Dynamic Spectrum Access.

Yifei Song, Hao-Hsuan Chang, Zhou Zhou, Shashank Jere, Lingjia Liu

CoRR, 2021

Edge Intelligence for Beyond-5G through Federated Learning.

Shashank Jere, Yang Yi

Proceedings of the 6th IEEE/ACM Symposium on Edge Computing, 2021

2020

Moving Toward Intelligence: Detecting Symbols on 5G Systems Through Deep Echo State Network.

Kangjun Bai, Yang Yi, Zhou Zhou, Shashank Jere, Lingjia Liu

IEEE J. Emerg. Sel. Topics Circuits Syst., 2020

Learning for Integer-Constrained Optimization through Neural Networks with Limited Training.

Zhou Zhou, Shashank Jere, Lizhong Zheng, Lingjia Liu

CoRR, 2020

Federated Learning in Mobile Edge Computing: An Edge-Learning Perspective for Beyond 5G.

Shashank Jere, Qiang Fan, Bodong Shang, Lianjun Li, Lingjia Liu

CoRR, 2020

RCNet: Incorporating Structural Information into Deep RNN for MIMO-OFDM Symbol Detection with Limited Training.

Zhou Zhou, Lingjia Liu, Shashank Jere, Jianzhong Zhang, Yang Yi

CoRR, 2020

Learning with Knowledge of Structure: A Neural Network-Based Approach for MIMO-OFDM Detection.

Zhou Zhou, Shashank Jere, Lizhong Zheng, Lingjia Liu

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2014

Extracting commuting patterns in railway networks through matrix decompositions.

Shashank Jere, Justin Dauwels, Muhammad Tayyab Asif, Nikola Mitrovic, Andrzej Cichocki, Patrick Jaillet

Proceedings of the 13th International Conference on Control Automation Robotics & Vision, 2014