Roads play a vital role to the people live in different places and, from day to day, they travel to schools, to work, to shops, and to transport their goods. Even in this modern world, roads remain one of the mediums used most frequently for travel and transportation. The computation of a shortest path between different locations appears to be a key problem in the road networks. The wide range ...

We propose to learn multiple local Mahalanobis distance metrics to perform knearest neighbor (kNN) classification of temporal sequences. Temporal sequences are first aligned by dynamic time warping (DTW); given the alignment path, similarity between two sequences is measured by the DTW distance, which is computed as the accumulated distance between matched temporal point pairs along the alignme...

We are dealing with the problem of enforcing certain level of consistency in Boolean satisfaction problems (SAT problems). As a starting point we took path-consistency which we made stronger by requiring a more restrictive condition on paths connecting consistent pairs of values. Unfortunately, we found that enforcing such a modified path-consistency is an NP-complete problem. However, the defi...

Link-based dissimilarity measures, such as shortest path or Euclidean commute time distance, base their distance on paths between nodes of a weighted graph. These measures are known to be better suited to data manifold with nonconvex-shaped clusters, compared to Euclidean distance, so that k-nearest neighbor (NN) search is improved in such metric spaces. In this paper we present a new link-base...

ABSTRACT. We consider the nearest-neighbor simple random walk on Z, d ≥ 2, driven by a field of i.i.d. random nearest-neighbor conductances ωxy ∈ [0, 1]. Apart from the requirement that the bonds with positive conductances percolate, we pose no restriction on the law of the ω’s. We prove that, for a.e. realization of the environment, the path distribution of the walk converges weakly to that of...

Nearest neighbor (NN) classifier with dynamic time warping (DTW) is considered to be an effective method for time series classification. The performance of NN-DTW is dependent on the DTW constraints because the NN classifier is sensitive to the used distance function. For time series classification, the global path constraint of DTW is learned for optimization of the alignment of time series by...

By repeatedly combining the source node's nearest neighbor, we propose a node combination (NC) method to implement the Dijkstra's algorithm. The NC algorithm finds the shortest paths with three simple iterative steps: find the nearest neighbor of the source node, combine that node with the source node, and modify the weights on edges that connect to the nearest neighbor. The NC algorithm is mor...

We study the skip-thought model proposed by Kiros et al. (2015) with neighborhood information as weak supervision. More specifically, we propose a skip-thought neighbor model to consider the adjacent sentences as a neighborhood. We train our skip-thought neighbor model on a large corpus with continuous sentences, and then evaluate the trained model on 7 tasks, which include semantic relatedness...