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Sensing, Recognition, and Prediction Methods / Predictive Modeling, Behavior Inference, and Trend Estimation Methods

Collision data in RFID sensing systems leads to unreliable channel estimation, affecting applications such as activity recognition.

lightbulbPractical problemPredictive Modeling, Behavior Inference, and Trend Estimation Methods

Collision data in RFID sensing systems leads to unreliable channel estimation, affecting applications such as activity recognition.

UbiComp '21Embracing Collisions to Increase Fidelity of Sensing Systems with COTS Tags

Similar questions

lightbulbPractical problemPredictive Modeling, Behavior Inference, and Trend Estimation Methods

When users converse with digital characters, systems struggle to accurately understand context, resulting in stilted interaction.

CUI '24Multimodal Dialog Act Classification for Conversations With Digital Characters

lightbulbPractical problemPredictive Modeling, Behavior Inference, and Trend Estimation Methods

Existing liquid identification technologies are costly, inaccurate, and poorly suited to everyday use.

UbiComp '24LiquImager: Fine-grained Liquid Identification and Container Imaging System with COTS WiFi Devices

lightbulbPractical problemPredictive Modeling, Behavior Inference, and Trend Estimation Methods

Users struggle to obtain precise, personalized real-time stress monitoring in practice.

UbiComp '24Unraveling Temporal Dependencies in Stress: Insights from Self-Reported Stress Data

lightbulbPractical problemPredictive Modeling, Behavior Inference, and Trend Estimation Methods

When slow devices participate in federated learning, training latency is high and personalized accuracy is poor.

UbiComp '24EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control

lightbulbPractical problemPredictive Modeling, Behavior Inference, and Trend Estimation Methods

Users have high churn rates in weight-loss apps, preventing health goals from being achieved.

CHI '24Predicting early user churn in a public digital weight loss intervention

lightbulbPractical problemPredictive Modeling, Behavior Inference, and Trend Estimation Methods

Data centers face high power consumption and unstable power supply costs, making energy savings difficult.

UbiComp '23LSTM Based Short-Term Data Center Electrical Consumption Forecasting

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EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control

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Predicting early user churn in a public digital weight loss intervention

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Amortized Inference with User Simulations

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Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships

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Speeding up Inference with User Simulators through Policy Modulation

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Modeling Touch Point Distribution with Rotational Dual Gaussian Model

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