Search Results - "Cho, Yae Jee"

Communication-Efficient and Model-Heterogeneous Personalized Federated Learning via Clustered Knowledge Transfer by Cho, Yae Jee, Wang, Jianyu, Chirvolu, Tarun, Joshi, Gauri

“…Personalized federated learning (PFL) aims to train model(s) that can perform well on the individual edge-devices' data where the edge-devices (clients) are…”
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Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning by Jee Cho, Yae, Gupta, Samarth, Joshi, Gauri, Yagan, Osman

“…Due to communication constraints and intermittent client availability in federated learning, only a subset of clients can participate in each training round…”
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Map-Based Millimeter-Wave Channel Models: An Overview, Data for B5G Evaluation and Machine Learning by Lim, Yeon-Geun, Cho, Yae Jee, Sim, Min Soo, Kim, Younsun, Chae, Chan-Byoung, Valenzuela, Reinaldo A.

“…Within the mm-Wave range of the B5G communication systems, there will appear many types of applications with different link types. In discussions on how to…”
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Relationship Between Cross-Polarization Discrimination (XPD) and Spatial Correlation in Indoor Small-Cell MIMO Systems by Lim, Yeon-Geun, Cho, Yae Jee, Oh, Taeckkeun, Lee, Yongshik, Chae, Chan-Byoung

“…In this letter, we provide a correlated channel model for a dual-polarization antenna in indoor small-cell multiple-input multiple-output (MIMO) systems. In an…”
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Effective Enzyme Deployment for Degradation of Interference Molecules in Molecular Communication by Yae Jee Cho, Yilmaz, H. Birkan, Weisi Guo, Chan-Byoung Chae

“…In molecular communication, the heavy tail nature of molecular signals causes inter-symbol interference (ISI). Because of this, it is difficult to decrease…”
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A machine learning approach to model the received signal in molecular communications by Yilmaz, H. Birkan, Changmin Lee, Yae Jee Cho, Chan-Byoung Chae

“…A molecular communication channel is determined by the received signal, which forms the basis for studies that are focusing on modulation, receiver design,…”
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Faster, Incentivized, and Efficient Federated Learning: Theory and Applications by Cho, Yae Jee

“…Artificial intelligence (AI) is becoming increasingly ubiquitous with a plethora of applications such as recommendation systems, image/video generation, or…”
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Effective inter‐symbol interference mitigation with a limited amount of enzymes in molecular communications by Cho, Yae Jee, Yilmaz, H. Birkan, Guo, Weisi, Chae, Chan‐Byoung

“…In molecular communication via diffusion (MCvD), the inter‐symbol interference (ISI) is a well‐known severe problem that deteriorates both data‐rate and link…”
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Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels by Cho, Yae Jee, Joshi, Gauri, Dimitriadis, Dimitrios

“…Many existing FL methods assume clients with fully-labeled data, while in realistic settings, clients have limited labels due to the expensive and laborious…”
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Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies by Cho, Yae Jee, Wang, Jianyu, Joshi, Gauri

“…Federated learning is a distributed optimization paradigm that enables a large number of resource-limited client nodes to cooperatively train a model without…”
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Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models by Cho, Yae Jee, Liu, Luyang, Xu, Zheng, Fahrezi, Aldi, Joshi, Gauri

“…Foundation models (FMs) adapt well to specific domains or tasks with fine-tuning, and federated learning (FL) enables the potential for privacy-preserving…”
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Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer by Cho, Yae Jee, Wang, Jianyu, Chiruvolu, Tarun, Joshi, Gauri

“…Personalized federated learning (FL) aims to train model(s) that can perform well for individual clients that are highly data and system heterogeneous. Most…”
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On the Convergence of Federated Averaging with Cyclic Client Participation by Cho, Yae Jee, Sharma, Pranay, Joshi, Gauri, Xu, Zheng, Kale, Satyen, Zhang, Tong

“…Federated Averaging (FedAvg) and its variants are the most popular optimization algorithms in federated learning (FL). Previous convergence analyses of FedAvg…”
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Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning by Cho, Yae Jee, Gupta, Samarth, Joshi, Gauri, Yağan, Osman

“…Due to communication constraints and intermittent client availability in federated learning, only a subset of clients can participate in each training round…”
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Maximizing Global Model Appeal in Federated Learning by Cho, Yae Jee, Jhunjhunwala, Divyansh, Li, Tian, Smith, Virginia, Joshi, Gauri

“…Federated learning typically considers collaboratively training a global model using local data at edge clients. Clients may have their own individual…”
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Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning by Cho, Yae Jee, Manoel, Andre, Joshi, Gauri, Sim, Robert, Dimitriadis, Dimitrios

“…Federated learning (FL) enables edge-devices to collaboratively learn a model without disclosing their private data to a central aggregating server. Most…”
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V2X Downlink Coverage Analysis with a Realistic Urban Vehicular Model by Cho, Yae Jee, Huang, Kaibin, Chae, Chan-Byoung

“…As the realization of vehicular communication such as vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) is imperative for the autonomous driving…”
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V2X Downlink Coverage Analysis with a Realistic Urban Vehicular Model by Cho, Yae Jee, Huang, Kaibin, Chae, Chan-Byoung

“…As the realization of vehicular communication is imperative for the autonomous driving cars, the understanding of realistic vehicle-to-everything (V2X) models…”
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RF Lens-Embedded Antenna Array for mmWave MIMO: Design and Performance by Cho, Yae Jee, Suk, Gee-Yong, Kim, Byoungnam, Kim, Dong Ku, Chae, Chan-Byoung

“…The requirement of high data rate in 5G calls for utilization of the mmWave frequency band. Researchers seeking to compensate for mmWave's high path loss have…”
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RF Lens-Embedded Antenna Array for mmWave MIMO: Design and Performance by Cho, Yae Jee, Suk, Gee-Yong, Kim, Byoungnam, Kim, Dong Ku, Chae, Chan-Byoung

“…The requirement of high data-rate in the fifth generation wireless systems (5G) calls for the ultimate utilization of the wide bandwidth in the mmWave…”
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