Give an efficient algorithm that takes a directed graph G = (V, E) and two vertices...
Please show your work 3. Give an efficient algorithm that takes as input a directed graph G-(V,E) with edges labeled with either 0 or 1, and vertices s and t that ouputs TRUE if and only if there is a path (not necessarily simple) that goes from s to t such that the binary sequence of edges in the path avoids the substring "11" and outputs FALSE otherwise. (For example, the string 10100010 avoids 11 but the string 00101101110 does...
Viterbi algorithm We can use dynamic programming on a directed graph G = (V, E) for speech recognition. Each edge (u, v) in E is labeled with a sound s(u, v) from a finite set S of sounds. The labeled graph is a formal model of a person speaking a restricted language. Each path in the graph starting from a distinguished vertex v0 in V corresponds to a possible sequence of sounds produced by the model. The label of a...
2. Let G = (V, E) be an undirected connected graph with n vertices and with an edge-weight function w : E → Z. An edge (u, v) ∈ E is sparkling if it is contained in some minimum spanning tree (MST) of G. The computational problem is to return the set of all sparkling edges in E. Describe an efficient algorithm for this computational problem. You do not need to use pseudocode. What is the asymptotic time complexity of...
3. The indegree of a vertex u is the number of incoming edges into u, .e, edges of the form (v,u) for some vertex v Consider the following algorithm that takes the adjacency list Alvi, v2, n] of a directed graph G as input and outputs an array containing all indegrees. An adjacency list Alvi, v.. /n] is an array indexed by the vertices in the graph. Each entry Alv, contains the list of neighbors of v) procedure Indegree(Alvi, v2,......
5. (10 pts) Give a concrete example of a directed and weighted graph G and two vertices u and v, where the Dijkstra's algorithm does not find the shortest path from u to v in G but the Bellman-Ford algorithm does. Obviously such a graph must have at least one negative- weight edge.
Problem 5. (12 marks) Connectivity in undirected graphs vs. directed graphs. a. (8 marks) Prove that in any connected undirected graph G- (V, E) with VI > 2, there are at least two vertices u, u є V whose removal (along with all the edges that touch them) leaves G still connected. Propose an efficient algorithm to find two such vertices. (Hint: The algorithm should be based on the proof or the proof should be based on the algorithm.) b....
Consider the following weighted, directed graph G. There are 7 vertices and 10 edges. The edge list E is as follows:The Bellman-Ford algorithm makes |V|-1 = 7-1 = 6 passes through the edge list E. Each pass relaxes the edges in the order they appear in the edge list. As with Dijkstra's algorithm, we record the current best known cost D[V] to reach each vertex V from the start vertex S. Initially D[A]=0 and D[V]=+oo for all the other vertices...
Problem 1: Given a graph G (V,E) a subset U S V of nodes is called a node cover if each edge in E is adjacent to at least one node in U. Given a graph, we do not know how to find the minimum node cover in an efficient manner. But if we restriet G to be a tree, then it is possible. Give a greedy algorithm that finds the minimum node cover for a tree. Analyze its correctness...
Consider a directed acyclic graph G = (V, E) without edge lengths and a start vertex s E V. (Recall, the length of a path in an graph without edge lengths is given by the number of edges on that path). Someone claims that the following greedy algorithm will always find longest path in the graph G starting from s. path = [8] Ucurrent = s topologically sort the vertices V of G. forall v EV in topological order do...
Give an example of a graph G with at least 10 vertices such that the greedy 2-approximation algorithm for Vertex-Cover given below is guaranteed to produce a suboptimal vertex cover. Algorithm Vertex CoverApprox(G): Input: A graph G Output: A small vertex cover C for G while G still has edges do select an edge e (v, w) of G add vertices v and w to C for each edge f incident to v or w do remove f from G...