'Kd trees' presentation slideshows

Instance based and Bayesian learning

Instance based and Bayesian learning. Kurt Driessens with slide ideas from a.o . Hendrik Blockeel , Pedro Domingos , David Page, Tom Dietterich and Eamon Keogh. Overview. Nearest neighbor methods Similarity Problems: dimensionality of data, efficiency, etc. Solutions:

720 views • 62 slides

Lecture outline

Lecture outline. Nearest-neighbor search in low dimensions kd-trees Nearest-neighbor search in high dimensions LSH Applications to data mining. Definition. Given: a set X of n points in R d Nearest neighbor: for any query point q ? R d return the point x ? X minimizing D(x,q)

552 views • 55 slides

Lecture outline

Lecture outline. Nearest-neighbor search in low dimensions kd-trees Nearest-neighbor search in high dimensions LSH Applications to data mining. Definition. Given: a set X of n points in R d Nearest neighbor: for any query point q ? R d return the point x ? X minimizing D(x,q)

664 views • 51 slides

Point Location Strategies

548 views • 48 slides

Estimating Performance of a Ray-Tracing ASIC Design

563 views • 40 slides

CS-378: Game Technology

476 views • 39 slides

Ray Tracing, Part 2

Christian Lauterbach COMP 770, 2/16/2009. Ray Tracing, Part 2. Overview. Acceleration structures Spatial hierarchies Object hierarchies Interactive Ray Tracing techniques Ray packets Optimized hierarchy construction. Last lecture. Ray Tracing For each pixel: generate ray

451 views • 28 slides

Supporting Animation and Interaction

Supporting Animation and Interaction. Ingo Wald SCI Institute, University of Utah wald@openrt.de. Supporting Animation and Interaction. Motivation Types of Animations Alternative Approaches Animated Scenes in OpenRT Practical Examples. The Need for Dynamic Scenes.

348 views • 25 slides

Efficient Nearest Neighbor Searching for Motion Planning

Anna Atramentov Dept. of Computer Science Iowa State University Ames, IA, USA. Steven M. LaValle Dept. of Computer Science University of Illinois Urbana, IL, USA. Efficient Nearest Neighbor Searching for Motion Planning. Support provided in part by an NSF CAREER award. Statistics

316 views • 20 slides

Computational Geometry

Computational Geometry. Piyush Kumar (Lecture 5: Range Searching). Welcome to CIS5930. Range Searching : recap. 1D Range search kD trees Range Trees Fractional Cascading. Range Searching. Preprocess a set P of objects for efficiently answering queries.

446 views • 17 slides

Computational Geometry

Computational Geometry. Piyush Kumar (Lecture 5: Range Searching). Welcome to CIS5930. Range Searching : recap. 1D Range search kD trees Range Trees Fractional Cascading. Range Searching. Preprocess a set P of objects for efficiently answering queries.

259 views • 17 slides