PDF-Coupled SemiSupervised Learning for Information Extraction Andrew Carlson Schoool of Computer

cmuedu Justin Betteridge Schoool of Computer Science Carnegie Mellon University Pittsburgh PA 15213 jbettercscmuedu Richard C Wang Schoool of Computer Science Carnegie Mellon University Pittsburgh PA 15213 rcwangcscmuedu Estevam R Hruschka Jr Federal. Efros Carnegie Mellon University Abstract This paper proposes a conceptually simple but surpris ingly powerful method which combines the effectiveness of a discriminative object detector with the explicit correspon dence offered by a nearestneighbor Efros Carnegie Mellon University Figure 1 In this paper we are interested in de64257ning visual similarity between images across different domains such as photos taken in different seasons paintings sketches etc What makes this challenging is that t We discuss the fundamental similarities between static algorithms eg A replanning algorithms eg D anytime algorithms eg ARA and anytime re planning algorithms eg AD We introduce the mo tivation behind each class of algorithms discuss their use on re ECT 1989 Carnegie Mellon University 89 10 10171 Appved for pus bc te Dtatzlbaton WUftitied brPage 2br Unclassified SECURITY CLASSIFICATION OF THIS PAGE REPORT DOCUMENTATION PAGE Ia JPOfT SECLINTY CLASSIFICATION lb RESTRICTIVE MARKINGS 2a SECURITY C scanfd val Carnegie Mellon return y Ax int matvecint A int x int y mallocNsizeofint int i j for i0 i for j0 j yi Aijxj return y brPage 5br Carnegie Mellon int p p mallocNsizeofint for i0 i pi mallocMsizeofint Carnegie Mellon int p p mallocN We present a general methodology for near optimal sensor placement in these and related problems We demonstrate that many realistic outbreak detection objectives eg de tection likelihood population a64256ected exhibit the prop erty of submodularity Floating Point. 15-213: Introduction to Computer Systems – Recitation. January 24, 2011. Today: Floating Point. Data Lab. Floating Point Basics. Representation. Interpreting the bits. Rounding. Floating Point Examples. Preferred Name Guidelines Guiding Principle* Carnegie Mellon University recognizes that students may wish to use a name other than their given names as recorded on offici al university documents. Whe Microstructure. -. Properties. Tensors and Anisotropy, Part 2. Profs. A. . D. Rollett, . M. . De . Graef. Microstructure. Properties. Processing. Performance. Last modified. : . 15. th. . Nov. ‘15. Networking Basics and Concurrent Programming. Shiva (. sshankar. ). Section . M. 2. Carnegie Mellon. Topics. Networking Basics. Concurrent Programming. Introduction to Proxy Lab. 3. Carnegie Mellon. Sockets. sniffed . the air, and still . sniffing. , looked down at the old dog. “God . awmighty. , that dog stinks. Get him . outa. . here, Candy! I don’t know nothing that . stinks . as bad as an old dog. You . If you’re trying to sell your house fast, you may have come across the term cash home buyer. The term refers to real estate investors who buy homes for cash. We are 412 Houses, leading cash home buyers in Pittsburgh, and we help people sell their distressed properties. https://www.412houses.com/ 27-731. Texture, Microstructure & Anisotropy. J.V. Gordon. With help from A.D. Rollett and Lazlo . Toth. Last revised: 6. th. Feb. ‘20. 2. Bibliography. U.F. . Kocks. , C. Tomé, H.-R. . Wenk. Pittsburgh’s leading cash buyer provides much-needed relief for distressed homeowners, helping them sell their properties at attractive prices.