'Level tree' presentation slideshows

Boosting (2)

426 views • 42 slides

I256: Applied Natural Language Processing

I256: Applied Natural Language Processing. Marti Hearst Sept 25, 2006. Shallow Parsing. Break text up into non-overlapping contiguous subsets of tokens. Also called chunking, partial parsing, light parsing. What is it useful for? Entity recognition people, locations, organizations

346 views • 19 slides

Buffered Steiner Trees for Difficult Instances

Buffered Steiner Trees for Difficult Instances. Charles J. Alpert, Gopal Gandham, Milos Hrkic, John Lillis, Jiang Hu, Andrew B. Kahng, Bao Liu, Stephen T. Quay, Sachin S. Sapatnekar, Andrew J. Sullivan. Late 1980s. Min-Cost Steiner Tree. Timing-driven Steiner Tree. Early 1990s.

197 views • 18 slides

Section 5: Performance

Section 5: Performance. Chris Zingraf. Overview:. This section measures the performance of MapReduce on two computations, Grep and Sort. These programs represent a large subset of real programs that MapReduce users have created. 5.1 Cluster Configuration The machines: .

251 views • 14 slides