4 citations · 10 across the 4 of their papers we have counts for
11 papers
On Extending NLP Techniques from the Categorical to the Latent Space: KL Divergence, Zipf's Law, and Similarity Search
Adam Hare, Yu Chen, Yinan Liu +2
Despite the recent successes of deep learning in natural language processing (NLP), there remains widespread usage of and demand for techniques that do not rely on machine learning…
Multi-IRS-assisted Multi-Cell Uplink MIMO Communications under Imperfect CSI: A Deep Reinforcement Learning Approach
Junghoon Kim, Seyyedali Hosseinalipour, Taejoon Kim +2
Applications of intelligent reflecting surfaces (IRSs) in wireless networks have attracted significant attention recently. Most of the relevant literature is focused on the single…
Frequency-based Automated Modulation Classification in the Presence of Adversaries
Rajeev Sahay, Christopher G. Brinton, David J. Love
Automatic modulation classification (AMC) aims to improve the efficiency of crowded radio spectrums by automatically predicting the modulation constellation of wireless RF signals.…
A Fast Graph Neural Network-Based Method for Winner Determination in Multi-Unit Combinatorial Auctions
Mengyuan Lee, Seyyedali Hosseinalipour, Christopher G. Brinton +2
The combinatorial auction (CA) is an efficient mechanism for resource allocation in different fields, including cloud computing. It can obtain high economic efficiency and user fle…
Federated Learning with Communication Delay in Edge Networks
Frank Po-Chen Lin, Christopher G. Brinton, Nicolò Michelusi
Federated learning has received significant attention as a potential solution for distributing machine learning (ML) model training through edge networks. This work addresses an im…
Fast-Convergent Federated Learning
Hung T. Nguyen, Vikash Sehwag, Seyyedali Hosseinalipour +3
Federated learning has emerged recently as a promising solution for distributing machine learning tasks through modern networks of mobile devices. Recent studies have obtained lowe…