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Found 10 papers, 1 papers with code
Unleashing the True Power of Age-of-Information: Service Aggregation in Connected and Autonomous Vehicles
With an increase in AoI, incremental service aggregation issues are observed with out-of-sequence information updates, which hampers the performance of low-latency applications in CAVs.
Unveiling Energy Efficiency in Deep Learning: Measurement, Prediction, and Scoring across Edge Devices
In this paper, we conduct a threefold study, including energy measurement, prediction, and efficiency scoring, with an objective to foster transparency in power and energy consumption within deep learning across various edge devices.
Confidence-based federated distillation for vision-based lane-centering
Machine learning-based steering angle prediction needs to consider the vehicle's limitation in uploading large amounts of potentially private data for model training.
EPAM: A Predictive Energy Model for Mobile AI
Predicting the energy consumption of these models, along with their different applications, such as vision and non-vision, requires a thorough investigation of their behavior using various processing sources.
Metamobility: Connecting Future Mobility with Metaverse
A Metaverse is a perpetual, immersive, and shared digital universe that is linked to but beyond the physical reality, and this emerging technology is attracting enormous attention from different industries.
Factored Conditional Filtering: Tracking States and Estimating Parameters in High-Dimensional Spaces
This paper introduces the factored conditional filter, a new filtering algorithm for simultaneously tracking states and estimating parameters in high-dimensional state spaces.
Towards a classification of connected components of the strata of $k$-differentials
A $k$-differential on a Riemann surface is a section of the $k$-th power of the canonical bundle.
Geometric Topology Algebraic Geometry Number Theory
Cold-start Playlist Recommendation with Multitask Learning
Playlist recommendation involves producing a set of songs that a user might enjoy.
Revisiting revisits in trajectory recommendation
Trajectory recommendation is the problem of recommending a sequence of places in a city for a tourist to visit.
Learning Points and Routes to Recommend Trajectories
Information about POIs are used to learn a POI ranking model that accounts for the start and end points of tours.
