Sequence Labelling 1: Part-of-Speech Tagging This time: Parts of Speech What are they useful for? Open and closed PoS classes PoS Tagsets The Penn Treebank Tagset PoS Tagging Sources of information for tagging A simple unigram tagger Evaluating taggers Data Science Group (Informatics) NLE/ANLP Autumn 2015 1 / 27 Parts of Speech Words can be […]
Journal of Machine Learning Research 15 (2014) 1929-1958 Submitted 11/13; Published 6/14 Dropout: A Simple Way to Prevent Neural Networks from Overfitting Nitish Srivastava Geoffrey Hinton Alex Krizhevsky Ilya Sutskever Ruslan Salakhutdinov Department of Computer Science University of Toronto 10 Kings College Road, Rm 3302 Toronto, Ontario, M5S 3G4, Canada. Editor: Yoshua Bengio nitish@cs.toronto.edu hinton@cs.toronto.edu
Due: 09:59 AM on Friday, Fri, Oct 11 Lab 09 – PicoFermiBagel Points: 100 points Objective: This assignment will demonstrate your knowledge of loops, classes, methods, and Java data types. About: You will write a Java program to play the game of Pico, Fermi, Bagel. Rules: Here are the rules of the game: 1. The
Assignment 2: COMP90043 Due Date: September 23, 2016 Assignment is worth 7.5% of the total marks 1. Answer all the questions. 2. A Discussion forum thread Assignment 2 has been created on LMS. Any clarification o↵ered on this forum will be considered as a part of the specification of the Assignment. 3. The total number
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GLIMPSE: A Tool to Search Through Entire File Systems Udi Manber and Sun Wu TR 93-34 October 1993 DEPARTMENT OF COMPUTER SCIENCE To appear in the 1994 Winter USENIX Technical Conference GLIMPSE: A Tool to Search Through Entire File Systems 1 Udi Manber Department of Computer Science University of Arizona Tucson, AZ 85721 udi@cs.arizona.edu Sun
Program Analysis Problem Sheet 1 Here is the Gale and Shapley algorithm for the Stable Match problem. Initialize each person to be free while there’s a free man who hasn’t proposed to every woman Choose one such man m Let w be 1st woman on m’s list to whom m not proposed if w is
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Games & AI #2 DIJKSTRA’S ALGORITHM Games & AI #2: Dijkstra’s Algorithm Patrick Dickinson This week 1. Look at an algorithm (Dijkstra’s) for solving general searches on graphs. 2. Try to understand how it works 3. Understand limitations 4. Think about how it could be used in games You will implement Dijkstra in workshop 2
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BARRIER & APPLICATION BROKEN BARRIERS BROADCASTED • • • • • BARRIER Sometimes when we use parallelized algorithm, we need to stop at some checkpoints. Next iteration relies on previous iteration. Need to wait for all the threads to complete their job. Barrier is a solution All the threads have to arrive at barrier before
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In [1]: import urllib2 #specify the url wiki = “http://guide.berkeley.edu/courses/compsci/” page = urllib2.urlopen(wiki) from bs4 import BeautifulSoup soup = BeautifulSoup(page, “lxml”) In [34]: res = [] for t in soup.find_all(‘h3’, class_=”courseblocktitle”): alls = t.find_all() res.append(‘ ‘.join(x.string for x in alls).replace(u’\xa0’, ‘ ‘)) # alls = soup.find_all(‘h3’, class_=”courseblocktitle”)[0].find_all() # ‘ ‘.join(x.string for x in alls).replace(u’\xa0’, ‘ ‘) In [35]:
Program Analysis Problem Sheet 11 1. The question considers the Ford-Fulkerson Algorithm. MaximumFlow(G, s, t, c, ): let f(e) = 0 for all e ∈ E while there is a path from s to t in the residual graph Gf let p be a simple path from s to t f ← augment(G, f, p)
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