Kondrak, Greg - Department of Computing Science, University of Alberta

• Multilingual Cognate Identification using Integer Linear Programming
• Lecture 25: Single-Source Shortest Paths Dijkstra's algorithm (correctness)
• CMPUT 204 Winter 2006 Department of Computing Science
• BENVENGUTS! Le faciada se disgela. Le beton se dissolve e lente
• A New Algorithm for the Alignment of Phonetic Sequences Grzegorz Kondrak
• Cognates and Word Alignment in Bitexts Grzegorz Kondrak
• Biomedical Term Recognition Using Discriminative Training Sittichai Jiampojamarn, Grzegorz Kondrak and Colin Cherry
• Lecture 18: Graph Basics Definitions
• Lecture 17: Dynamic Programming Dynamic programming
• Bootstrapping a Stochastic Transducer for ArabicEnglish Transliteration Extraction
• Ngram similarity and distance Grzegorz Kondrak
• A Comparison of Sentiment Analysis Techniques: Polarizing Movie Blogs
• Cognates and Word Alignment in Bitexts Grzegorz Kondrak
• CMPUT 204 Winter 2006 Department of Computing Science
• Biomedical Term Recognition With the Perceptron HMM Algorithm
• Lecture 6: Solving Recurrences Iterated substitution
• Identification of Confusable Drug Names: A New Approach and Evaluation Methodology
• CMPUT 204 Winter 2006 Department of Computing Science
• Cognates Can Improve Statistical Translation Models Grzegorz Kondrak
• Combining Evidence in Cognate Identi cation Grzegorz Kondrak
• Determining Recurrent Sound Correspondences by Inducing Translation Models
• Lecture 19: Graph Traversal Depth First search
• Learning a Spelling Error Model from Search Query Logs Farooq Ahmad
• A Fast Method for Parallel Document Identification Jessica Enright and Grzegorz Kondrak
• Identifying Cognates by Phonetic and Semantic Similarity Grzegorz Kondrak
• Multilingual Cognate Identification using Integer Linear Programming
• Phonetic alignment and similarity Grzegorz Kondrak
• Lecture 14: Divide and Conquer Example 1: Multiplication of large integers
• Creating a Comparative Dictionary of TotonacTepehua Grzegorz Kondrak
• Phonetic alignment and similarity Grzegorz Kondrak
• Computing Word Similarity and Identifying Cognates with Pair Hidden Markov Models
• Lecture 24: Single-Source Shortest Paths Single-source shortest paths
• Unsupervised Labeling of Noun Clusters Theresa Jickels and Grzegorz Kondrak
• Lecture 7: Heaps Max-Heapify
• Lecture 15: Dynamic Programming Dynamic programming
• Lecture 2: Basic concepts Random access machine
• Labio-dentalDentalBilabial Palato-alveolar Alveolar Retroflex
• Identifying Complex Sound Correspondences in Bilingual Wordlists
• Applying ManytoMany Alignments and Hidden Markov Models to LettertoPhoneme Conversion
• Identifying Complex Sound Correspondences in Bilingual Wordlists
• CMPUT 204 Winter 2006 Department of Computing Science
• Lecture 9: Heapsort Priority Queues
• SubstringBased Transliteration Tarek Sherif and Grzegorz Kondrak
• Lecture 4: Some proof techniques Proofs by counter-example, contrapositive, contra-
• Unsupervised Labeling of Noun Clusters Theresa Jickels and Grzegorz Kondrak
• Biomedical Term Recognition Using Discriminative Training Sittichai Jiampojamarn, Grzegorz Kondrak and Colin Cherry
• Evaluation of Several Phonetic Similarity Algorithms on the Task of Cognate Identification
• N-Gram Similarity and Distance Grzegorz Kondrak
• Identifying Cognates by Phonetic and Semantic Similarity Grzegorz Kondrak
• Lecture 1: Introduction Welcome to CMPUT 204 -Algorithms I
• Lecture 5: Some proof techniques Merge Sort
• Lecture 10: Quicksort Quicksort algorithm
• Lecture 11: Quicksort: Average case Quicksort: AC running time
• Lecture 12: Lower bound for sorting Recursion tree
• Lecture 13: Greedy Method Example 1: Fractional Knapsack
• Lecture 20: Biconnected Components Definition
• Lecture 21: Breadth-First Search Algorithm
• Lecture 22: Directed Graphs Traversal
• CMPUT 204 Winter 2006 Department of Computing Science
• Statistical Machine Translation Translation without Understanding
• A New Algorithm for the Alignment of Phonetic Sequences Grzegorz Kondrak
• Algorithms for Language Reconstruction Grzegorz Kondrak
• Lecture 8: Building Heaps Max-Heapify
• Lecture 16: Dynamic Programming Dynamic programming
• Lecture 3: Asymptotic notations Running time --order of growth in input size
• A Comparison of Sentiment Analysis Techniques: Polarizing Movie Blogs
• Lecture 23: Minimum Spanning Trees Minimum Spanning Trees