Search Results for author:
Found 9 papers, 2 papers with code
EHL*: Memory-Budgeted Indexing for Ultrafast Optimal Euclidean Pathfinding
The Euclidean Shortest Path Problem (ESPP), which involves finding the shortest path in a Euclidean plane with polygonal obstacles, is a classic problem with numerous real-world applications.
Tracking Progress in Multi-Agent Path Finding
Multi-Agent Path Finding (MAPF) is an important core problem for many new and emerging industrial applications.
Multi-Target Search in Euclidean Space with Ray Shooting (Full Version)
The Euclidean shortest path problem (ESPP) is a well studied problem with many practical applications.
Unsupervised Space Partitioning for Nearest Neighbor Search
We achieve the above edge by formulating a multi-objective custom loss function that does not need ground truth labels to quantify the quality of a given data-space partition, making it entirely unsupervised.
DeepAltTrip: Top-k Alternative Itineraries for Trip Recommendation
In this paper, we propose a deep learning-based framework, called DeepAltTrip, that learns to recommend top-k alternative itineraries for given source and destination POIs.
An Experimental Analysis of Indoor Spatial Queries: Modeling, Indexing, and Processing
Indoor location-based services (LBS), such as POI search and routing, are often built on top of typical indoor spatial queries.
Databases Data Structures and Algorithms
CommuNety: A Deep Learning System for the Prediction of Cohesive Social Communities
Traditional approaches rely on the analysis of text data related to users to accomplish this task.
Comparing Alternative Route Planning Techniques: A Comparative User Study on Melbourne, Dhaka and Copenhagen Road Networks
Motivated by this, in this paper, we present a user study conducted on the road networks of Melbourne, Dhaka and Copenhagen that compares the quality (as perceived by the users) of the alternative routes generated by four of the most popular existing approaches including the routes provided by Google Maps.
An Efficient Approximation Algorithm for Multi-criteria Indoor Route Planning Queries
The experiments demonstrate that our algorithm is highly efficient and produces quality results.
