Efficient Continuous K-Nearest Neighbor Query Processing over Moving Objects with Uncertain Speed and Direction Yuan-Ko Huang, Shi-Jei Liao, and Chiang Lee Department of Computer Science and Information

Source URL: i.cs.hku.hk

NNH: Improving Performance of Nearest-Neighbor Searches Using Histograms (Full Version. UCI Technical Report, DecLiang Jin1 , Nick Koudas2 , and Chen Li1 1

Source URL: flamingo.ics.uci.edu

MEMOCODE 2014 Design Contest: k-Nearest Neighbors with Mahalanobis Distance Metric Peter Milder Department of Electrical and Computer Engineering Stony Brook University Stony Brook, NY 11794–2350

Source URL: www.ece.stonybrook.edu

• Statistics
• Data analysis
• Computing
• Search algorithms
• Covariance and correlation
• Multivariate statistics
• Machine learning
• Mahalanobis distance
• Statistical distance
• Xeon
• Nearest neighbor search
• K-nearest neighbors algorithm

A Collaborative Filtering Approach to Real-Time Hand Pose Estimation Chiho Choi, Ayan Sinha, Joon Hee Choi, Sujin Jang, Karthik Ramani Purdue University West Lafayette, IN 47907, USA {chihochoi, sinha12, choi240, jang64,

Source URL: engineering.purdue.edu

• Artificial intelligence
• Computer vision
• Statistics
• Search algorithms
• Mathematics
• Robot control
• Computational neuroscience
• Convolutional neural network
• Random sample consensus
• Nearest neighbor search
• K-nearest neighbors algorithm
• Recommender system

Scalable Continuous Range Monitoring of Moving Objects in Symbolic Indoor Space Bin Yang1,2 Hua Lu1 Christian S. Jensen1 1

Source URL: people.cs.aau.dk

• Computer science
• Mathematics
• Computing
• Data mining
• Discrete geometry
• Nearest neighbor search
• Numerical analysis
• Range query
• Bin

Real-Time Community Detection in Large Social Networks on a Laptop Ben Chamberlain Clive Humby

Source URL: www.mlgworkshop.org

• Mathematics
• Information science
• Graph theory
• Hashing
• Search algorithms
• Hash functions
• MinHash
• Networks
• Jaccard index
• Nearest neighbor search
• Community structure
• Graph

Fast Hierarchical Clustering and Other Applications of Dynamic Closest Pairs David Eppstein∗ Abstract dynamic closest pair problem. It can be solved by brute force 2 We develop data structures for dynamic closest pair

Source URL: bioinfo.ict.ac.cn

• Mathematics
• Statistics
• Applied mathematics
• Data mining
• Search algorithms
• Approximation algorithms
• Discrete geometry
• Nearest neighbor search
• Numerical analysis
• Hierarchical clustering
• Cluster analysis
• K-means clustering

1 Continuous Skyline Queries for Moving Objects Zhiyong Huang, Hua Lu, Beng Chin Ooi, and Anthony K. H. Tung Abstract— The literature on skyline algorithms has so far dealt

Source URL: people.cs.aau.dk

• Computing
• Information science
• Data management
• Information retrieval
• Search algorithms
• SQL
• Skyline operator
• Skyline
• Nearest neighbor search
• Data stream management system
• PT2
• Kinetic data structure

Distance sampling Len Thomas, Stephen T. Buckland, Kenneth P. Burnham, David R. Anderson, Jeffrey L. Laake, David L. Borchers & Samantha Strindberg Volume 1, pp 544–552 in Encyclopedia of Environmetrics

Source URL: distancesampling.org

• Environmental statistics
• Statistics
• Academia
• Knowledge
• Sampling techniques
• Monte Carlo methods
• Transect
• Distance sampling
• Sampling
• Line-intercept sampling
• Resampling
• Nearest neighbor search

Continuous Skyline Queries for Moving Objects Zhiyong Huang Hua Lu Beng Chin Ooi

Source URL: www.comp.nus.edu.sg

• Computing
• Data management
• Information science
• Data
• SQL
• Skyline operator
• Skyline
• Nearest neighbor search
• Data stream management system
• PT2
• Kinetic data structure