PPT-Fine-Grained Visual Identification using Deep and Shallow

Andréia Marini Adviser Alessandro L Koerich Postgraduate Program in Computer Science PPGIa Pontifical Catholic University of Paraná PUCPR Outline Motivation The Challenge. PUBLIC SWIM FEES ARE LISTED BELOW 1145 AM 115 PM Rec Fitness 1145 AM115 PM WHOLE POOL Rec Fitness 1145 AM115 PM WHOLE POOL Rec Fitness 1145 AM115 PM WHOLE POOL Rec Fitness 1145 AM115 PM WHOLE POOL Longcourse Rec Fitness 1145 AM115 PM WHOLE POOL Liwen. Sun, Michael J. Franklin, Sanjay Krishnan, Reynold S. . Xin†. UC . Berkeley and †. Databricks. Inc. .. VLDB 2014. March 17, 2015. Heymo. Kou. Introduction. Overview. Workload Analysis. The Partitioning Problem. Xen. Bhanu Vattikonda. with . Sambit. Das and . Hovav. . Shacham. 2. Motivation . Project goals. Goals of the paper. Discussion . Future work. Motivation. 3. Recent research efforts have shown that covert channel attacks are possible in the cloud using fine grained timers . Zechao Shang. 1. , . Feifei. Li. 2. , Jeffrey Xu Yu. 1. Zhiwei. Zhang. 3. , Hong Cheng. 1. . 1. The Chinese University of Hong Kong. . 2. University of Utah. 3. Hong Kong Baptist University. not. ISHAY BE’ERY. ELAD KNOLL. OUTLINES. . Motivation. Model . c. ompression: mimicking large networks:. FITNETS : HINTS FOR THIN DEEP NETS . (A. Romero, 2014). DO DEEP NETS REALLY NEED TO BE DEEP . (Rich Caruana & Lei Jimmy Ba 2014). Recognition(. 细粒度分类. ) . 沈志强. Datasets. . -- Caltech-UCSD Bird-200-2011. Number of categories: 200. Number of images: 11,788. Annotations per image: 15 Part Locations, 1 Bounding Box. Factors Affecting Reliable Word Sense Annotation. Susan . Windisch. Brown, Travis Rood, and Martha Palmer. University of Colorado at Boulder. Annotators in their little nests agree;. And ‘tis a shameful sight,. . NFs. . for. . Flexiable. . per-flow. . Customization. Wei Zhang, Jinho Hwang, Shriram Rajagopal, k.k. . ramakrishnan. and . timothy. . wood. – conext 2016. From: Class Wide Monolithic NFs . Landscape Ecology. Representation of scale-dependent landscape . structures responded to by a wren and a hawk.. Carolina. Wren. Red-. tailed. Hawk. Hostetler and Holling 2000. r vs. k selection life history strategies. Joel Kamdem Teto. z. Introduction. Fine-grained Multithreading . The ability of a single core to handle multiple thread by:. Providing a register for each thread. Dividing the pipeline bandwidth into N part . Lijie. Chen. MIT. Today’s Topic. Background. . What is Fine-Grained Complexity?. The Methodology of Fine-Grained Complexity. Frontier: Fine-Grained Hardness for Approximation Problems. The Connection. Andréia Marini . Adviser: Alessandro L. . Koerich. Postgraduate . Program in Computer Science (. PPGIa. ) . Pontifical . Catholic University of . Paraná (PUCPR). Outline. Motivation. The . Challenge. Heng. . Ji (UIUC. ). 1. What are “entities”?. [Main meaning]. - unique world bodies with (non-unique) names, such as. people, organizations, locations. e.g. . Washington County. [Extended meaning – information extraction]. Krossfjord. and . Fensfjord. formations, Troll Field, northern North Sea. Richard Brown. Tectonic Location. Located on the . Horda. Platform. This is on the eastern margin of the Viking . Graben.