helpResearch questionPredictive Modeling, Behavior Inference, and Trend Estimation Methods
How can dynamic clustering and optimized broadcast frequency improve efficiency and accuracy of mobile federated learning?Sensing, Recognition, and Prediction Methods / Predictive Modeling, Behavior Inference, and Trend Estimation Methods
How can dynamic clustering and optimized broadcast frequency improve efficiency and accuracy of mobile federated learning?
Similar questions
helpResearch questionPredictive Modeling, Behavior Inference, and Trend Estimation Methods
How can multimodal information (text, audio, video) improve dialogue act classification performance?CUI '24Multimodal Dialog Act Classification for Conversations With Digital Characters
helpResearch questionPredictive Modeling, Behavior Inference, and Trend Estimation Methods
How does cross-modal attention enhance multimodal data performance in dialogue act classification?CUI '24Multimodal Dialog Act Classification for Conversations With Digital Characters
helpResearch questionPredictive Modeling, Behavior Inference, and Trend Estimation Methods
Can real-time dialogue act prediction be achieved through multimodal data?CUI '24Multimodal Dialog Act Classification for Conversations With Digital Characters
helpResearch questionPredictive Modeling, Behavior Inference, and Trend Estimation Methods
How can COTS WiFi devices simultaneously identify and image liquids and containers?helpResearch questionPredictive Modeling, Behavior Inference, and Trend Estimation Methods
How can electromagnetic scattering models compensate for precise modeling gaps of centimeter-scale container effects on signals?helpResearch questionPredictive Modeling, Behavior Inference, and Trend Estimation Methods
Can combining deep learning with physical modeling improve accuracy and robustness of liquid identification and container imaging?Related papers
UbiComp 2024
LiquImager: Fine-grained Liquid Identification and Container Imaging System with COTS WiFi Devices
Fei Shang, Panlong Yang, Dawei Yan
UbiComp 2024
EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control
Xiaochen Li, Sicong Liu, Zimu Zhou
CHI 2024
Predicting early user churn in a public digital weight loss intervention
Robert Jakob, Nils Lepper, Elgar Fleisch
CHI 2023
Amortized Inference with User Simulations
Hee-Seung Moon, Antti Oulasvirta, Byungjoo Lee
CHI 2022
Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships
Eunice Jun, Audrey Seo, Jeffrey Heer
CHI 2022
Speeding up Inference with User Simulators through Policy Modulation
Hee-Seung Moon, Seungwon Do, Wonjae Kim
UIST 2021
Modeling Touch Point Distribution with Rotational Dual Gaussian Model
Yan Ma, Shumin Zhai, IV Ramakrishnan