On Distance to Monotonicity and Longest Increasing Subsequence of a Data Stream Funda Ergun∗ Abstract In this paper we consider problems related to the sortedness of a data stream. First we investigate the problem of

Source URL: www.cs.sfu.ca

Single-Pass List Partitioning Leonor Frias ∗ Universitat Polit`ecnica de Catalunya Dep. de Llenguatges i Sistemes Inform`atics Jordi Girona Salgado, Barcelona, Spain

Source URL: algo2.iti.kit.edu

• Mathematics
• Computational complexity theory
• Dynamic programming
• Discrete mathematics
• Combinatorics
• Analysis of algorithms
• Algorithm
• Mathematical logic
• Theoretical computer science
• Time complexity
• FisherYates shuffle
• Longest increasing subsequence

An Algorithm for Differential File Comparison J. W. Hunt Department of Electrical Engineering, Stanford University, Stanford, California M. D. McIlroy Bell Laboratories, Murray Hill, New Jersey 07974

Source URL: www.cs.dartmouth.edu

• Mathematics
• Dynamic programming
• Combinatorics
• Discrete mathematics
• Formal languages
• Data differencing
• HuntMcIlroy algorithm
• Longest increasing subsequence
• Longest common subsequence problem
• Subsequence
• Diff utility
• Data comparison

A = a x aa m if and only if there is a mapping F: {1, 2, . . . , p} ~ {1, 2, . . . , m} such that f(i) = k only if c~ is ak and F is a m o n o t o n e strictly increasing function (i.e. F(i) = u, F ( j ) = v, a

Source URL: bioinfo.ict.ac.cn

• Dynamic programming
• Combinatorics
• Subsequence
• Longest common subsequence problem
• Longest increasing subsequence
• HuntMcIlroy algorithm

CS 170 Algorithms Spring 2009

Source URL: www-inst.eecs.berkeley.edu

• Control theory
• Mathematical optimization
• Operations research
• Combinatorics
• Longest increasing subsequence
• Algorithm
• Supercomputer
• Mathematics
• Computing
• Dynamic programming

UC Berkeley—CS 170: Efficient Algorithms and Intractable Problems Lecturer: David Wagner Handout 13 March 13, 2003

Source URL: www.cs.berkeley.edu

• Control theory
• Longest common subsequence problem
• Algorithm
• Substring
• Longest common substring problem
• Fibonacci number
• Overlapping subproblems
• Longest increasing subsequence
• Dynamic programming
• Mathematics
• Applied mathematics

Journal of Computational and Applied Mathematics–105 www.elsevier.com/locate/cam Hydrodynamical methods for analyzing longest increasing subsequences a

Source URL: dutiosb.twi.tudelft.nl

• Probability theory
• Dynamic programming
• Longest increasing subsequence
• Poisson process
• Point process
• Convergence of random variables
• Permutation
• Statistics
• Stochastic processes
• Combinatorics

June 2014 • Volume 7 • Number 5 To Foster and Nurture Girls’ Interest in Mathematics An Interview Interview with Marie Vitulli, Part 2 Finding the Maximum Subsequence, Part 1

Source URL: www.girlsangle.org

• Subsequence
• Algorithm
• Addition
• Number
• Longest increasing subsequence
• Matrix chain multiplication
• Mathematics
• Brahmagupta
• Dynamic programming

Algorithms Lecture 3: Backtracking [Fa’14] ’Tis a lesson you should heed, Try, try again;

Source URL: web.engr.illinois.edu

• Search algorithms
• Computability theory
• Theory of computation
• Programming idioms
• Backtracking
• Recursion
• Eight queens puzzle
• Tree traversal
• Longest increasing subsequence
• Mathematics
• Applied mathematics
• Theoretical computer science

Algorithms Lecture 5: Dynamic Programming [Fa’14] Those who cannot remember the past are doomed to repeat it. — George Santayana, The Life of Reason, Book I:

Source URL: web.engr.illinois.edu

• Dynamic programming
• Mathematical logic
• Operations research
• Programming idioms
• Algorithm
• Levenshtein distance
• Recursion
• Longest increasing subsequence
• Fibonacci number
• Mathematics
• Applied mathematics
• Theoretical computer science