PPT-Dimension reduction techniques for

l p 1ltplt2 with applications Yair Bartal LeeAd Gottlieb Hebrew U Ariel University Introduction Fundamental result in dimension reduction Johnson Lindenstrauss Lemma JL84 for Euclidean space. High-dimensional Data Analysis. Jong Youl Choi, . Seung-Hee. . Bae. , Judy . Qiu. , . and Geoffrey Fox. School of Informatics and Computing. Pervasive Technology Institute. Indiana University. S. A. of . L. p. Yair. . Bartal. Lee-Ad Gottlieb. Ofer. Neiman. Embedding and Distortion. L. p. spaces: . L. p. k. is the metric space . Let (. X,d. ) be a finite metric space. A map f:X. →. . L. p. Alexandr. . Andoni. (MSR). Definition by example. Problem. : Compute the diameter of a set . S. , of size . n. , living in . d. -dimensional . ℓ. 1. d. Trivial solution: . O(d * n. 2. ) . time. Will see solution in . via Interpolation. Seung-Hee. . Bae. , . Jong. Youl Choi, Judy . Qiu. , and Geoffrey Fox. School of Informatics and Computing. Pervasive Technology Institute. Indiana University. S. A. L. S. A. project. reviews, new methods of reduction, fixation and techniques. The overall picture is one of some confusion but two elementary points of universal agreement are seen to emerge : reduction must be perfect Sublinear. Algorithms:. Euclidean space: . dimension reduction and NNS. Alex Andoni. (MSR SVC). A Sketching Problem. 2. Sketching:. :objects . short bit-strings. given . . and . . should be able to deduce if . Developed by the:. University of Wisconsin Oshkosh. and. Wisconsin Department of Health Services. Learning Points. Recognize our reactions to stress. Explore techniques for stress relief. Incorporate stress reduction practices into our daily lives. Yining Wang. , Yu-Xiang Wang, . Aarti. Singh. Machine Learning Department. Carnegie . mellon. university. 1. Subspace Clustering. 2. Subspace Clustering Applications. Motion Trajectories tracking. 1. John A. Lee, Michel Verleysen, . Chapter4 . 1. Distance Preservation. دانشگاه صنعتي اميرکبير. (. پلي تکنيک تهران). 2. The motivation behind distance preservation is that any . 2. Alex Andoni. Plan. 2. Dimension reduction. Application: Numerical Linear Algebra. Sketching. Application: Streaming. Application: Nearest Neighbor Search. and more…. Dimension reduction: . linear . .. Dr. Archana . Kumari. Asstt. . Professor cum Junior Scientist. Veterinary Surgery and Radiology. BVC, BASU, Patna. PRINCIPALOF FRACTURE MANAGEMENT. 4R. Recognition. Reduction. . Retention . High-dimensional Data Analysis. Jong Youl Choi, . Seung-Hee. . Bae. , Judy . Qiu. , . and Geoffrey Fox. School of Informatics and Computing. Pervasive Technology Institute. Indiana University. S. A. Metric . Embeddings. COMS E6998-9. . F15. Administrivia. , Plan. PS2:. Pick up after class. 120->144 auto extension. Plan:. Least Squares Regression (finish). Metric . Embeddings. “reductions for distances”. . — Chapter 3 —. Data Warehouse and OLAP Technology: An Overview. 2. Chapter 3: Data Warehousing and OLAP Technology: An Overview. What is a data warehouse? . A multi-dimensional data model. Data warehouse architecture.