PPT-Theory of Locality Sensitive Hashing

CS246 Mining Massive Datasets Jure Leskovec Stanford University httpcs246stanfordedu Recap Finding similar documents Task Given a large number N in the millions or billions of documents find near duplicates. Optimization. Techniques. . Presented by . Preethi Rajaram. CSS 548 Introduction to Compilers . Professor Carol Zander. Fall 2012 . Why?. Processor Speed . -. increasing at a faster rate than the memory speed. A General Analytical Study. Yongkun. Li, . Patrick P. C. Lee. , John C. S. . Lui. , . Yinlong. Xu. The Chinese . University . of Hong . Kong. University of Science and Technology of China. . 1. SSD Storage. Zhenhua . Guo. , Geoffrey Fox, Mo Zhou. Outline. Introduction. Data Locality and Fairness. Experiments. Conclusions. MapReduce Execution Overview. 3. Google File System. Read input data. Data locality. Approximate Near Neighbors. Ilya Razenshteyn (CSAIL MIT). Alexandr. . Andoni. (Simons Institute). Approximate Near Neighbors (ANN). Dataset:. . n. points in . d. dimensions. Query:. a point within . Lecture 6: Locality Sensitive Hashing (LSH). Nearest Neighbor . Given a set P of n points in R. d. Nearest Neighbor . Want to build a data structure to answer nearest neighbor queries. Voronoi. Diagram. Practical methodology for Healthy Economies . You can do it! . No really, you can! . HERE’S . HOW. MAKE A PLAN - STRATEGIZE. MAKE A BUDGET. ASSESS YOUR CURRENT SITUATION. IDENTIFY WHAT IS WORKING. Cyryptocurrency Project Proposal - Spring 2015. SHA Use in Bitcoin. SHA256 used heavily as bitcoin’s underlying cryptographic hashing function. Two examples (of many) are its use in the Merkle tree hash, as well as the proof of work calculation. Madhu. . Sudan. Harvard. April 9, 2016. Skoltech: Locality in Coding Theory. 1. Error-Correcting Codes. (Linear) Code . .. : Finite field with . elements.. . block length. . message length. : Rate of . Consider a set of data with N data items stored in some data structure. We must be able to insert, delete & search for items. What are possible ways to do this? What is the complexity of each structure & method ?. What is a hashing function?. Fingerprint for a given piece of data. Typically generated by a mathematical algorithm. Produces a fixed length string as its . output. Hashes are sometimes . called a . checksum or message digests. CS246: Mining Massive Datasets. Jure Leskovec, . Stanford University. http://cs246.stanford.edu. Recap: Finding similar documents. Task:. . Given a large number (. N. in the millions or billions) of documents, find “near duplicates”. Daniel Burk. What is a Predictive Model?. A GIS based model attempting to determine fossil locality potential. 1. Start with known fossil localities. 2. Compare their characteristics to other places. Nhan Nguyen. & . Philippas. . Tsigas. ICDCS 2014. Distributed Computing and Systems. Chalmers University of Technology. Gothenburg, Sweden. Our contributions: a concurrent hash table. Nhan D. Nguyen. Amjad. . Daoud. , Ph.D.. http://iswsa.acm.org/mphf. Practical Perfect Hashing for very large Key-Value Databases . Abstract. This presentation describes a practical algorithm for perfect hashing that is suitable for very large KV (key, value)...