PDF-Active LeZi: An Incremental Parsing Algorithm for Sequential Predictio

Given the resources in a practical situation the predictor that is capable of possibly meeting these requirements has to be a member of the set of all possible finite state machines FSM. Ling 571. Deep Processing Techniques for NLP. January 12, 2011. Roadmap . Motivation: . Parsing (In) efficiency. Dynamic Programming. Cocke. -. Kasami. -Younger Parsing Algorithm . Chomsky Normal Form. CS 4705. Julia Hirschberg. 1. Some slides adapted from Kathy McKeown and Dan Jurafsky. Syntactic Parsing. Declarative . formalisms like CFGs, FSAs define the . legal strings of a language. -- but only tell you whether a given string is legal in a particular language. for Scaling Sparse Optimization. Tyler B. Johnson and Carlos . Guestrin. University of Washington. Very important to machine learning. Our focus is constrained convex optimization. Number of constraints can be very large!. Jeffrey Lidz, Aaron Steven White & Rebecca Baier jlidz@umd.edu aswhite@umd.edu rbaier@umd.edu Department of Linguistics University of Maryland, College Park 1401 Marie Mount Hall Uni versity of Mary : A Compositional Hypervisor for Software-Defined Networks. Xin . Jin. , Jennifer . Gossels. , Jennifer Rexford, David . Walker. Princeton University. Coordinating Control-plane Modules. Compositional Network Hypervisor. General Context-Free Grammars. Why Parse General Grammars. Can be difficult or impossible to make grammar unambiguous. thus LL(k) and LR(k) methods cannot work, . for such ambiguous grammars. Some inputs are more complex than simple programming languages. Top-down vs. bottom-up parsing. Top-down . vs. bottom-up . parsing. Ex. Ex. Ex. Ex. +. Nat. *. Nat. Nat. Ex. Ex. . . . Nat. | . (. Ex. ). | . Ex. . +. . Ex. | . Ex. . *. . Ex. Matched input string. Evaluation. . Sequential: runtime (execution time). . Ts. =T (. InputSize. ). . Parallel: runtime (. s. tart-->last PE ends). . Tp. =T (. InputSize,p,architecture. ). . Note: Cannot be Evaluated in Isolation from the Parallel architecture. 1. Some slides . adapted from Julia Hirschberg and Dan . Jurafsky. To view past videos:. http://. globe.cvn.columbia.edu:8080/oncampus.php?c=133ae14752e27fde909fdbd64c06b337. Usually available only for 1 week. Right now, available for all previous lectures. CS 268 @ Gates 219. October 19, 3:00 – 4:20. Richard Zhang. (for Leo G.). 1. Disclaimer: All figures in the slides are for illustration only. Best approximations were attempted, but preciseness or correctness of the geometric constructions should not be assumed.. CS 4705. Julia Hirschberg. 1. Some slides adapted from Kathy McKeown and Dan Jurafsky. Syntactic Parsing. Declarative . formalisms like CFGs, FSAs define the . legal strings of a language. -- but only tell you whether a given string is legal in a particular language. Lecture 1: . Introduction, basic probability theory. , incremental . parsing. Florian. Jaeger & Roger . Levy. LSA 2011 Summer Institute. Boulder, CO. 8 July 2011. What this class . will. and . will not . How Long will an Algorithm take?. When we are processing an array, we have seen the searching using sequential search is much slower than binary search.. How Long will an Algorithm take?. For Sequential search:. Parsing Giuseppe Attardi Dipartimento di Informatica Università di Pisa Università di Pisa Question Answering at TREC Consists of answering a set of 500 fact-based questions, e.g. “When was Mozart born