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Found 6 papers, 1 papers with code
DeepTagRec: A Content-cum-User based Tag Recommendation Framework for Stack Overflow
In this paper, we develop a content-cum-user based deep learning framework DeepTagRec to recommend appropriate question tags on Stack Overflow.
Asynchronous Multi Agent Active Search
Active search refers to the problem of efficiently locating targets in an unknown environment by actively making data-collection decisions, and has many applications including detecting gas leaks, radiation sources or human survivors of disasters using aerial and/or ground robots (agents).
Multi-Agent Active Search using Detection and Location Uncertainty
We then build a decision making algorithm on this inference method that uses Thompson sampling to enable decentralized multi-agent active search.
Cost Aware Asynchronous Multi-Agent Active Search
Multi-agent active search requires autonomous agents to choose sensing actions that efficiently locate targets.
MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning
We then show that our model-based meta-learning approach is cost-effective in intervening on bandit agents with unseen explore-exploit strategies.
Decentralized Multi-Agent Active Search and Tracking when Targets Outnumber Agents
Multi-agent multi-target tracking has a wide range of applications, including wildlife patrolling, security surveillance or environment monitoring.
