PPT-Approximate Dynamic Programmin

g and aCGH denoising Charalampos Babis E Tsourakakis ctsourakmathcmuedu Machine Learning Seminar 10 th January 11 Machine Learning Lunch Seminar. INTRODUCTIO N Ove th las 2 years th combinatio o faste computers mor reliabl e data an improve algorithm ha resulte i th nearroutin solutio o man y intege program o practica interest Intege programmin model ar use d a wid variet o apphcations includ INTRODUCTIO N Th proble o simultaneousl stabilizin a whol famil o plant ha receive con derabl attentio fo man years Th presen wor wa motivate b a recen t resul 1 tha provide a relativel simpl algorith fo solvin th followin prob lem Give a famil o pl 601 Roaring Brook TOWNSHIP LINE Amwell Road Rt 514 BUCKEYE PIPELINE TEXAS EASTERN PIPELINE MONTGOMERY TOWNSHIP HILLSBOROUGH TOWNSHIP Ent ance Zion Road East Mountain Road East Mountain Roosevelt TOWNSHIP LINE Zion Road Clark Held Biggs Featherbed Pl University of Washington. Adrian Sampson, . Hadi. Esmaelizadeh,. 1. Michael . Ringenburg. , . Reneé. St. Amant,. 2. . Luis . Ceze. , . Dan Grossman. , Mark . Oskin. , Karin Strauss,. 3. and Doug Burger. Michael . Carbin. with . Sasa. . Misailovic. , Hank Hoffmann. , . Deokhwan. . Kim, . Stelios. . Sidiroglou. , Martin . Rinard. MIT. Challenges for Programming. Expression (specifying approximations). Hardware: Challenges and Opportunities. Author. : Bingsheng He. (Nanyang Technological University, Singapore) . Speaker. : . Jiong . He . (Nanyang Technological University, Singapore. ). 1. What is Approximate Hardware?. Constant. Imply. Specify. Civil . implicate. Series. Component. Approximate. Principal. therefore. Write the word and its definition. Constant: Not changing or varying – The water was at a constant temperature. Christopher . Ré. and Dan . Suciu. University of Washington. Approximate Lineage in One Slide. Lineage (Provenance) . In QP used to track correlations. Explain query/view results. VLDBs have lots of lineage. 77 Approximate cost of units in above image*(kitchen in image is Edwardian Style)MDF CARCASESMELAMINE CARCASES EDWARDIAN STYLE BRAMPTON STYLE (for Cock-Bead detail to framewo Abbas Rahimi, . Andrea . Marongiu. ,. . Rajesh K. Gupta, Luca . Benini. UC San Diego, and . University of Bologna . Micrel.deis.unibo.it. /. MultiTherman. variability.org. Outline. Introduction. and . Andrew B. Kahng, . Seokhyeong Kang . VLSI CAD LABORATORY, . UC. San Diego. 49. th. Design Automation Conference. June 6. th. , 2012. Outline. Background and Motivation. Accuracy Configurable Adder Design. Computation Circuits. Wei-Ting Jonas Chan. 1. , Andrew B. Kahng. 1. , . Seokhyeong Kang. 1. , . Rakesh. Kumar. 2. , and John Sartori. 3. 1. VLSI . CAD LABORATORY, . UC San Diego. 2. PASSAT GROUP, Univ. of Illinois. Matagorda County, TX. CE 394K Fall 2017. Sydney Kase. Essential Questions. Why does FEMA create the . NFHL. and . FIRM. maps?. Why does it take so long to produce effective floodplain maps?. What does the . dynamic data structures. Shachar. Lovett. IAS. Ely . Porat. Bar-. Ilan. University. Synergies in lower bounds, June 2011. Information theoretic lower bounds. Information theory. is a powerful tool to prove lower bounds, e.g. in data structures.