Search Results for author:
Found 6 papers, 1 papers with code
TopoNav: Topological Navigation for Efficient Exploration in Sparse Reward Environments
Additionally, TopoNav incorporates intrinsic motivation to guide exploration toward relevant regions and frontier nodes in the topological map, addressing the challenges of sparse extrinsic rewards.
HeteroEdge: Addressing Asymmetry in Heterogeneous Collaborative Autonomous Systems
Finally, we propose and optimize a novel parameter split-ratio, which indicates the proportion of the data required to be offloaded to another device while considering the networking bandwidth, busy factor, memory (CPU, GPU, RAM), and power constraints of the devices in the testbed.
An Edge-Cloud Integrated Framework for Flexible and Dynamic Stream Analytics
In this paper, we study how to best leverage edge and cloud resources to achieve better accuracy and latency for stream analytics using a type of RNN model called long short-term memory (LSTM).
Top-K Ranking Deep Contextual Bandits for Information Selection Systems
Contextual multi-armed bandit has been widely used for learning to filter contents and prioritize according to user interest or relevance.
Reproducible and Portable Big Data Analytics in the Cloud
To tackle these problems, we leverage serverless computing and containerization techniques for automated scalable execution and reproducibility, and utilize the adapter design pattern to enable application portability and reproducibility across different clouds.
Deep Upper Confidence Bound Algorithm for Contextual Bandit Ranking of Information Selection
Contextual multi-armed bandits (CMAB) have been widely used for learning to filter and prioritize information according to a user's interest.
