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15 February 2023

  • 10:2510:25, 15 February 2023 diff hist +1,086 N Rod-Cutting ProblemCreated page with "{{DISPLAYTITLE:Rod-Cutting Problem (Rod-Cutting Problem)}} == Description == Given a rod of length $n$, and prices $p_i$ for which one can sell a segment of the rod of length $i$ ($1 \leq i \leq n$), find the splitting of the rod for which one can earn the most money once they sell the rod segments produced. == Parameters == <pre>n: length of rod</pre> == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year..."
  • 10:2510:25, 15 February 2023 diff hist +2,925 N Discrete Logarithm Over Finite FieldsCreated page with "{{DISPLAYTITLE:Discrete Logarithm Over Finite Fields (Logarithm Calculations)}} == Description == Let $F_{p^n}$ denote the finite field of $p^n$ elements, where $p$ is a prime. Let $x$ be a generator for the multiplicative group of $F_{p^n}$. The discrete logarithm problem over $F_{p^n}$ is to compute, for any given nonzero $h \in F_{p^n}$, the least nonnegative integer $e$ such that $x^e=h$. In this context we shall write $e=\log_x h$. == Parameters == <pre>n: numb..."
  • 10:2510:25, 15 February 2023 diff hist +41 N Pattern Matching on HypertextRedirected page to Sequence-To-Graph Alignment current Tag: New redirect
  • 10:2510:25, 15 February 2023 diff hist +1,159 N Sequence-To-Graph AlignmentCreated page with "{{DISPLAYTITLE:Sequence-To-Graph Alignment (Sequence-to-Graph Alignment)}} == Description == This is pattern matching where you are given a pattern and a hypertext graph. The hypertext model is that the text forms a graph of $N$ nodes and $E$ edges, where a string is stored inside each node, and the edges indicate alternative texts that may follow the current node. The pattern is still a simple string of length $m$. It is also customary to transform this graph into a o..."
  • 10:2510:25, 15 February 2023 diff hist +799 N Integer Relation Among IntegersCreated page with "{{DISPLAYTITLE:Integer Relation Among Integers (Integer Relation)}} == Description == Given a vector $x \in \mathbb{Z}^n$, find an integer relation, i.e. a non-zero vector $m \in \mathbb{Z}^n$ such that $<x, m> = 0$ == Related Problems == Generalizations: Integer Relation Among Reals == Parameters == <pre>n: dimensionality of vectors</pre> == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Ti..."
  • 10:2510:25, 15 February 2023 diff hist +794 N Integer Relation Among RealsCreated page with "{{DISPLAYTITLE:Integer Relation Among Reals (Integer Relation)}} == Description == Given a vector $x \in \mathbb{R}^n$, find an integer relation, i.e. a non-zero vector $m \in \mathbb{Z}^n$ such that $<x, m> = 0$ == Related Problems == Subproblem: Integer Relation Among Integers == Parameters == <pre>n: dimensionality of vectors</pre> == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !!..."
  • 10:2510:25, 15 February 2023 diff hist +1,457 N Determinant of Matrices with Integer EntriesCreated page with "{{DISPLAYTITLE:Determinant of Matrices with Integer Entries (Determinant of Matrices with Integer Entries)}} == Description == Calculate the determinant of a given matrix with integer matrices. For such matrices, the determinant is also an integer. == Parameters == <pre>n: dimension of matrix</pre> == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! Approximation Factor !! Model !! R..."
  • 10:2510:25, 15 February 2023 diff hist +986 N Undirected Wiener IndexCreated page with "{{DISPLAYTITLE:Undirected Wiener Index (Wiener Index)}} == Description == Calculate the sum of the lengths of the shortest paths between all pairs of vertices in an undirected graph (typically in the chemical graph representing the non-hydrogen atoms in the molecule). == Related Problems == Related: Minimum Wiener Connector Problem == Parameters == <pre>n: number of vertices (number of non-hydrogen atoms in the molecule)</pre> == Table of Algorithms == Cur..."
  • 10:2510:25, 15 February 2023 diff hist +632 N Minimum Wiener Connector ProblemCreated page with "{{DISPLAYTITLE:Minimum Wiener Connector Problem (Wiener Index)}} == Description == Given a connected graph $G = (V, E)$ and a set $Q \subseteq V$ of query vertices, find a subgraph of $G$ that connects all query vertices and has minimum Wiener index. == Related Problems == Related: Undirected Wiener Index == Parameters == <pre>n: number of vertices m: number of edges q: number of query vertices</pre> == Table of Algorithms == Currently no algorithms in our..."
  • 10:2510:25, 15 February 2023 diff hist +25 N Max CutRedirected page to Maximum Cut current Tag: New redirect
  • 10:2510:25, 15 February 2023 diff hist +671 N Maximum CutCreated page with "{{DISPLAYTITLE:Maximum Cut (Maximum Cut)}} == Description == Given a graph $G=(V, E)$ with edge weights $c_e > 0$ for all $e\in E$, find a cut $\delta(W)$ such that $c(\delta(W)):=\Sigma_{e\in \dela(W)} c_e$ is as large as possible. == Parameters == <pre>n: number of vertices m: number of edges</pre> == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! Approximation Factor !! Model !!..."
  • 10:2510:25, 15 February 2023 diff hist +905 N D-Neighborhood of a StringCreated page with "{{DISPLAYTITLE:d-Neighborhood of a String (d-Neighborhood of a String)}} == Description == Given a DNA string pattern and an integer $d$, find the collection of strings that are within a $d$-neighborhood of the given pattern. A $d$-neighborhood is the set of all $k$-mers whose Hamming distance from the pattern is at most $d$. == Parameters == <pre>n: length of string d: neighborhood distance threshold sigma: size of alphabet</pre> == Table of Algorithms == {| cla..."
  • 10:2510:25, 15 February 2023 diff hist +1,789 N SLAM AlgorithmsCreated page with "{{DISPLAYTITLE:SLAM Algorithms (SLAM Algorithms)}} == Description == Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! Approximation Factor !!..."
  • 10:2510:25, 15 February 2023 diff hist +36 N OGMRedirected page to Occupancy Grid Mapping current Tag: New redirect
  • 10:2510:25, 15 February 2023 diff hist +1,060 N Occupancy Grid MappingCreated page with "{{DISPLAYTITLE:Occupancy Grid Mapping (Occupancy Grid Mapping)}} == Description == Assuming a robot's pose is known, generate a occupancy grid mapping of the area. The occupancy grid is a multidimensional random field that maintains stochastic estimates of the occupancy state of the cells in a spatial lattice. To construct a sensor-derived map of the robot’s world, the cell state estimates are obtained by interpreting the incoming range readings using probabilistic s..." current
  • 10:2510:25, 15 February 2023 diff hist +33 N Illumination MappingRedirected page to Environment Mapping current Tag: New redirect
  • 10:2510:25, 15 February 2023 diff hist +33 N Reflection MappingRedirected page to Environment Mapping current Tag: New redirect
  • 10:2510:25, 15 February 2023 diff hist +1,914 N Environment MappingCreated page with "{{DISPLAYTITLE:Environment Mapping (Texture Mapping)}} == Description == Texture mapping means the mapping of a function onto a surface in 3D. The domain of the function can be one, two, or three dimensional, and it can be represented by either an array or a mathematical function. The source image (texture) is mapped onto a surface in 3D object space, which is then mapped to the destination image (screen) by the viewing projection. Texture space is labeled $(u, v)$, o..." current
  • 10:2510:25, 15 February 2023 diff hist +908 N RasterizationCreated page with "{{DISPLAYTITLE:Rasterization (Rasterization)}} == Description == Raster-scan displays are most commonly driven by a frame buffer, a memory that stores the color value for every picture element on the screen and refreshes the display continuously. The process of generating these picture clement values from a geometric description of the image is known as rasterization. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" s..." current
  • 10:2510:25, 15 February 2023 diff hist +20 N Partially Observable Markov Decision ProcessRedirected page to POMDPs current Tag: New redirect
  • 10:2510:25, 15 February 2023 diff hist +2,598 N POMDPsCreated page with "{{DISPLAYTITLE:POMDPs (POMDPs)}} == Description == At (discrete) time step $t$, the environment is assumed to be in some state $X_t$. The agent then performs an action (control) $A_t$, whereupon the environment (stochastically) changes to a new state $X_{t+1}$. The agent doesn’t see the environment state, but instead receives an observation $Y_t$, which is some (stochastic) function of $X_t$. (If $Y_t = X_t$, the POMDP reduces to a fully observed MDP.) In addition, t..." current
  • 10:2510:25, 15 February 2023 diff hist +1,759 N Clock Synchronization in Distributed SystemsCreated page with "{{DISPLAYTITLE:Clock Synchronization in Distributed Systems (Clock Synchronization in Distributed Systems)}} == Description == The difference between the largest and the smallest clock values among all stations in a Mobile Ad Hoc Network (MANET) is called the maximum clock offset. The goal is to minimize the maximum clock offset. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%"..."
  • 10:2510:25, 15 February 2023 diff hist +4,955 N Mesh SimplificationCreated page with "{{DISPLAYTITLE:Mesh Simplification (Mesh Simplification)}} == Description == Given a surface mesh, accurately simplify it so that you may render the mesh accurately with less computing power. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! Approximation Factor !! Model !! Reference |- | Coplanar facets merging - M.J. De Haemer and M.J. Zy..." current
  • 10:2510:25, 15 February 2023 diff hist +3,912 N Image SegmentationCreated page with "{{DISPLAYTITLE:Image Segmentation (Image Segmentation)}} == Description == Image segmentation is the division of an image into different regions, each having certain properties. It is the first step of image analysis which aims at either a description of an image or a classification of the image if a class label is meaningful. An example of the former is the description of an office scene. An example of the latter is the classification of the image of a cancerous cell...."
  • 10:2510:25, 15 February 2023 diff hist +2,564 N Point-in-PolygonCreated page with "{{DISPLAYTITLE:Point-in-Polygon (Point-in-Polygon)}} == Description == With a given polygon $P$ and an arbitrary point $q$, determine whether point $q$ is enclosed by the edges of the polygon. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! Approximation Factor !! Model !! Reference |- | Ray casting algorithm Shimrat; M (Point-in-Polygon..."
  • 10:2510:25, 15 February 2023 diff hist +1,641 N Specular ReflectionCreated page with "{{DISPLAYTITLE:Specular Reflection (Texture Mapping)}} == Description == Texture mapping means the mapping of a function onto a surface in 3D. The domain of the function can be one, two, or three dimensional, and it can be represented by either an array or a mathematical function. The source image (texture) is mapped onto a surface in 3D object space, which is then mapped to the destination image (screen) by the viewing projection. Texture space is labeled $(u, v)$, o..."
  • 10:2510:25, 15 February 2023 diff hist +2,186 N Diffuse ReflectionCreated page with "{{DISPLAYTITLE:Diffuse Reflection (Texture Mapping)}} == Description == Texture mapping means the mapping of a function onto a surface in 3D. The domain of the function can be one, two, or three dimensional, and it can be represented by either an array or a mathematical function. The source image (texture) is mapped onto a surface in 3D object space, which is then mapped to the destination image (screen) by the viewing projection. Texture space is labeled $(u, v)$, ob..." current
  • 10:2510:25, 15 February 2023 diff hist +47 N CPSPRedirected page to Cyclic Peptide Sequencing Problem current Tag: New redirect
  • 10:2510:25, 15 February 2023 diff hist +1,136 N Cyclic Peptide Sequencing ProblemCreated page with "{{DISPLAYTITLE:Cyclic Peptide Sequencing Problem (Cyclic Peptide Sequencing Problem)}} == Description == Given an experimental $MS^3$ spectrum $S$, find a cyclic peptide $P$ maximizing the number of shared masses between $S$ and the theoretical spectrum of $P$. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! Approximation Factor !! Model !! R..."
  • 10:2510:25, 15 February 2023 diff hist +1,820 N Distributed Locking AlgorithmsCreated page with "{{DISPLAYTITLE:Distributed Locking Algorithms (Distributed Locking Algorithms)}} == Description == The purpose of a lock is to ensure that among several nodes that might try to do the same piece of work, only one actually does it (at least only one at a time). That work might be to write some data to a shared storage system, to perform some computation, to call some external API, or suchlike. At a high level, there are two reasons why you might want a lock in a distrib..."
  • 10:2510:25, 15 February 2023 diff hist +2,203 N Texture SynthesisCreated page with "{{DISPLAYTITLE:Texture Synthesis (Texture Synthesis)}} == Description == Given a texture sample, synthesize a new texture that, when perceived by a human observer, appears to be generated by the same underlying stochastic process. == Parameters == <pre>n: number of pixels</pre> == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! Approximation Factor !! Model !! Reference |- | tre..."
  • 10:2510:25, 15 February 2023 diff hist +538 N Image CompositingCreated page with "{{DISPLAYTITLE:Image Compositing (Image Compositing)}} == Description == Image compositing is the act of creating a single image from multiple images. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! Approximation Factor !! Model !! Reference |- | Petro Vlahos Algorithm || 1985..." current
  • 10:2510:25, 15 February 2023 diff hist +1,312 N InDegree AnalysisCreated page with "{{DISPLAYTITLE:InDegree Analysis (Link Analysis)}} == Description == A simple heuristic that can be viewed as the predecessor of all Link Analysis Ranking algorithms is to rank the pages according to their popularity (also referred to as visibility (Marchiori 1997)). The popularity of a page is measured by the number of pages that link to this page. We refer to this algorithm as the InDegree algorithm, since it ranks pages according to their in-degree in the graph $G$...."
  • 10:2510:25, 15 February 2023 diff hist +1,331 N All Maximal Non-Branching Paths in a GraphCreated page with "{{DISPLAYTITLE:All Maximal Non-Branching Paths in a Graph (All Maximal Non-Branching Paths in a Graph)}} == Description == A node $v$ in a directed graph $G$ is called a 1-in-1-out node if its indegree and outdegree are both equal to 1, i.e., $in(v) = out(v) = 1$. We can rephrase the definition of a "maximal non-branching path" from the main text as a path whose internal nodes are 1-in-1-out nodes and whose initial and final nodes are not 1-in-1-out nodes. The proble..."
  • 10:2410:24, 15 February 2023 diff hist +3,921 Motif SearchNo edit summary
  • 10:2410:24, 15 February 2023 diff hist +2,285 N Weighted Set-CoveringCreated page with "{{DISPLAYTITLE:Weighted Set-Covering (The Set-Covering Problem)}} == Description == The set-covering problem where each set $s\in S$ is assigned a weight and the goal is to find the minimum weight sub-collection of $S$ that covers the universe. == Related Problems == Subproblem: Unweighted Set-Covering == Parameters == <pre>n: number of elements in the universe m: number of sets in the collection d: size of the largest set in collection H(x): the xth Harmonic..."
  • 10:2410:24, 15 February 2023 diff hist +2,315 N Unweighted Set-CoveringCreated page with "{{DISPLAYTITLE:Unweighted Set-Covering (The Set-Covering Problem)}} == Description == Given a universe $U$, i.e. a set of elements $\{1, 2, \ldots, n\}$, and a collection $S$ of $m$ sets whose union is the universe, identify the smallest sub-collection of $S$ whose union is the universe. == Related Problems == Generalizations: Weighted Set-Covering == Parameters == <pre>U: the universe of elements to be covered S: the collection of sets n: number of elements..."
  • 10:2410:24, 15 February 2023 diff hist +1,531 N Optimal Policies for MDPsCreated page with "{{DISPLAYTITLE:Optimal Policies for MDPs (Optimal Policies for MDPs)}} == Description == In an MDP, a policy is a choice of what action to choose at each state An Optimal Policy is a policy where you are always choosing the action that maximizes the “return”/”utility” of the current state. The problem here is to find such an optimal policy from a given MDP. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" styl..."
  • 10:2410:24, 15 February 2023 diff hist +3,398 N Filtering Problem (Stochastic Processes)Created page with "{{DISPLAYTITLE:Filtering Problem (Stochastic Processes) (Filtering Problem (Stochastic Processes))}} == Description == The filtering problem is to obtain the best linear estimate $\hat{z}_t$ of $z_t$ based on the past observations ($y_s | s\leq t)$. Abstractly, the solution to the problem of filtering corresponds to explicitly computing $\hat{z}_t = P_t^y(z_t)$ where $P_t^y$ is the projection operator onto the Hilbert space $H_t^y$. == Parameters == No parameters..."
  • 10:2410:24, 15 February 2023 diff hist +943 N CullingCreated page with "{{DISPLAYTITLE:Culling (Culling)}} == Description == Culling is the process of rejecting primitives or objects in their entireity before rendering in the case that they would not be shown in the view, reducing unnecessary computations. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! Approximation Factor !! Model !! Reference |- | view fru..." current
  • 10:2410:24, 15 February 2023 diff hist +2,855 N Blob DetectionCreated page with "{{DISPLAYTITLE:Blob Detection (Feature Detection)}} == Description == The regions or points which have noticeable difference with their surroundings is called blob. Blob detection is the problem of detecting such blobs in a given image. == Related Problems == Related: Corner Detection == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! App..."
  • 10:2410:24, 15 February 2023 diff hist +3,600 N Corner DetectionCreated page with "{{DISPLAYTITLE:Corner Detection (Feature Detection)}} == Description == Conventionally, a corner is defined as the intersection point or the junction point between two or more straight line edges (i.e. edges which have discontinuities along a straight line). Corner detection is the problem of detecting such corners in a given image. == Related Problems == Related: Blob Detection == Parameters == No parameters found. == Table of Algorithms == {| class="wiki..."
  • 10:2410:24, 15 February 2023 diff hist +1,534 N Matrix FactorizationCreated page with "{{DISPLAYTITLE:Matrix Factorization (Collaborative Filtering)}} == Description == Collaborative filtering is a technique used in recommendation systems. It analyzes relationships between users and interdependencies among products to identify new user-item associations. A method of collaborative filtering uses matrix factorization. In its basic form, matrix factorization characterizes both items and users by vectors of factors inferred from item rating patterns. == Pa..."
  • 10:2410:24, 15 February 2023 diff hist +3,043 N Maximum Likelihood Methods in Unknown Latent VariablesCreated page with "{{DISPLAYTITLE:Maximum Likelihood Methods in Unknown Latent Variables (Maximum Likelihood Methods in Unknown Latent Variables)}} == Description == In this problem, the goal is to compute maximum-likelihood estimates when the observations can be viewed as incomplete data. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width="100%" ! Name !! Year !! Time !! Space !! Approximation Factor !!..."
  • 10:2410:24, 15 February 2023 diff hist +5,649 N Mesh ParameterizationCreated page with "{{DISPLAYTITLE:Mesh Parameterization (Mesh Parameterization)}} == Description == Given any two surfaces with similar topology it is possible to compute a one-to-one and onto mapping between them. If one of these surfaces is represented by a triangular mesh, the problem of computing such a mapping is referred to as mesh parameterization. == Parameters == No parameters found. == Table of Algorithms == {| class="wikitable sortable" style="text-align:center;" width=..."
  • 10:2410:24, 15 February 2023 diff hist +2,686 N Hyperbolic Spline InterpolationCreated page with "{{DISPLAYTITLE:Hyperbolic Spline Interpolation (Hyperbolic Spline Interpolation)}} == Description == The problem of restoring complex curves and surfaces from discrete data so that their shape is preserved is called isogeometric interpolation. A very popular tool for solving this problem are hyperbolic splines in tension, which were introduced in 1966 by Schweikert. These splines have smoothness sufficient for many applications; combined with algorithms for the automat..."
  • 10:2410:24, 15 February 2023 diff hist +35 N Record MatchingRedirected page to Duplicate Elimination current Tag: New redirect
  • 10:2410:24, 15 February 2023 diff hist +35 N Object IdentificationRedirected page to Duplicate Elimination current Tag: New redirect
  • 10:2410:24, 15 February 2023 diff hist +35 N Instance IdentificationRedirected page to Duplicate Elimination current Tag: New redirect
  • 10:2410:24, 15 February 2023 diff hist +35 N De-DuplicationRedirected page to Duplicate Elimination current Tag: New redirect

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