'Hierarchical' presentation slideshows

Functional Discourse Grammar and constituent order typology

Functional Discourse Grammar and constituent order typology. Kees Hengeveld. Introduction. In Functional Discourse Grammar (FDG), constituent order is taken care of in a novel way in two different senses:

1.14k views • 95 slides

QoS Support in Operating Systems

1.03k views • 67 slides

Agenda

634 views • 58 slides

Part 1: Bag-of-words models

710 views • 48 slides

Monitoring Change Through Hierarchical Segmentation of Remotely Sensed Image Data

Monitoring Change Through Hierarchical Segmentation of Remotely Sensed Image Data. James C. Tilton Mail Code 606* NASA GSFC Greenbelt, MD 20771 James.C.Tilton@nasa.gov. William T. Lawrence Natural Sciences Bowie State University Bowie, MD 20715 wlawrence@bowiestate.edu.

608 views • 44 slides

Modeling the Structure of the Sea Anemone and Sea Star Using Hierarchical Implicit Surfaces by

Modeling the Structure of the Sea Anemone and Sea Star Using Hierarchical Implicit Surfaces by Xikun Liang, Mai Ali Nur and Brian Wyvill Department of Computer Science University of Calgary, Alberta, Canada. Overview. Introduction Related Works

570 views • 37 slides

Theory of Multicore Algorithms

Theory of Multicore Algorithms. Jeremy Kepner and Nadya Bliss MIT Lincoln Laboratory HPEC 2008

419 views • 29 slides

Iterative Optimization and Simplification of Hierarchical Clusterings

Iterative Optimization and Simplification of Hierarchical Clusterings. Doug Fisher Department of Computer Science, Vanderbilt University Journal of Artificial Intelligence Research, 4 (1996) 147-179 Presented by: Biyu Liang. Outline. Introduction Generating Initial Hierarchical Clustering

407 views • 28 slides

Zhao Dong 1 , Jan Kautz 2 , Christian Theobalt 3 Hans-Peter Seidel 1

Zhao Dong 1 , Jan Kautz 2 , Christian Theobalt 3 Hans-Peter Seidel 1. Interactive Global Illumination Using Implicit Visibility. 1 MPI Informatik Germany. 2 University College London UK. 3 Stanford University US. Motivation. Global Illumination (GI) Effects.

432 views • 27 slides

672 views • 26 slides

Clustering

Clustering. Jarno Tuimala. Clustering. Aim Grouping objects (genes or chips) into clusters so that the objects inside one cluster are more closely related to each other than to objects in other clusters Exploratory data analysis View all data simultaneously

301 views • 17 slides

Respectful Relationships in the Maternity Service

264 views • 17 slides

Computer Architecture The Concept

322 views • 14 slides

Creating a Multi-Purpose First Person Shooter Bot with Reinforcement Learning

Creating a Multi-Purpose First Person Shooter Bot with Reinforcement Learning. IEEE Symposium On Computational Intelligence and Games pp. 143-150 Dec. 2008 Authors: M. McPartland and M. Gallagher Presented by Chien-Erh Huang. 1. 2. 3. 4. 5. Introduction. Background. Method. Results.

270 views • 12 slides

Spatial Indexing I

Spatial Indexing I. Point Access Methods. Spatial Indexing. Point Access Methods (PAMs) vs Spatial Access Methods (SAMs) PAM: index only point data Hierarchical (tree-based) structures Multidimensional Hashing Space filling curve SAM: index both points and regions Transformations

248 views • 11 slides

Cluster Algorithms

Cluster Algorithms. Sep 12 th 2006. Goal of Clustering. To group similar board games. Hundreds of board games are compared and grouped into clusters such that they are close enough to be converted from one board game to another. Clustering Types. Exclusive Clustering Eg: K means

174 views • 7 slides

Abstract

Magnetic Ordering of CoCl 2 -GIC: a Spin Ceramic -Hierarchical Successive Transitions and the Intermediate Glassy Phase- by *)M. Suzuki, I.S. Suzuki and **)M. Matsuura *)Dept ? . Phys., SUNY Binghamton and **)Fukui Univ. Tech. Abstract

102 views • 1 slides

Abstract

Magnetic Ordering of CoCl 2 -GIC: a Spin Ceramic -Hierarchical Successive Transitions and the Intermediate Glassy Phase- by *)M. Suzuki, I.S. Suzuki and **)M. Matsuura *)Dept ? . Phys., SUNY Binghamton and **)Fukui Univ. Tech. Abstract

127 views • 1 slides

The Scotch Cattle 1816 -1849

The Scotch Cattle 1816 -1849. Monmouthshire South Breconshire (Black Domain) Welsh speaking areas. Coal and Iron. Truck System. Long Pay. Debt. What were the causes of the Scotch Cattle?. Lack of Job security. Attempt to impose order + organise strikes. Well organised

112 views • 1 slides

A Symbolic Model Checking Framework for Hierarchical Systems

A Symbolic Model Checking Framework for Hierarchical Systems. Truong Khanh Nguyen 1 , Jun Sun 2 , Yang Liu 1 , and Jin Song Dong 1 1 National University of Singapore 2 Singapore University of Technology and Design. Introduction. Approach.

142 views • 1 slides