A) Financial market analysis B) Computer networks C) Handwriting recognition D) Electrical grids
A) Dijkstra's algorithm B) Christofides algorithm C) Prim's algorithm D) Kruskal's algorithm
A) K-means clustering B) DBSCAN C) Mean-shift clustering D) Single-linkage clustering
A) Voltage regulation B) Signal amplification C) Efficient multiple constant multiplications D) Heat dissipation reduction
A) Visualizing relationships between stocks B) Calculating tax liabilities C) Predicting daily stock volatility D) Automated high-frequency trading
A) Dynamic routing protocol design B) Encryption key distribution C) Constructing trees for broadcasting D) Firewall configuration
A) Urban population census B) Meteorological forecasting C) Socio-geographic regionalisation D) Political lobbying
A) Frame rate optimization B) Curvilinear feature extraction C) Pixel resolution upscaling D) Color space normalization
A) Measuring homogeneity B) Testing electrical resistance C) Calculating thermal conductivity D) Identifying atomic composition
A) Quadratic assignment problem B) Maximum bipartite matching C) Minimum-cost weighted perfect matching D) Linear programming relaxation
A) It belongs to exactly one MST. B) It is excluded from all MSTs. C) It belongs to all MSTs of the graph. D) It belongs to no MSTs.
A) Each such edge is contained in some minimum spanning tree. B) They must all be in every MST. C) None of these edges are in any MST. D) Only one of them is in any MST.
A) This edge is only included if the graph is a tree. B) This edge is included in any MST. C) This edge is never included in an MST. D) This edge is only included if there is only one vertex.
A) Vojtěch Jarník B) Dijkstra C) Otakar Borůvka D) Prim
A) It doubles. B) It remains the same. C) It is reduced by at least half. D) It increases by one.
A) O(m log n) B) O(n log n) C) O(n2) D) O(m log m)
A) Otakar Borůvka B) Kruskal C) Dijkstra D) Vojtěch Jarník
A) By contracting all vertices. B) One edge at a time from an arbitrary vertex. C) By removing the heaviest edges. D) By adding all edges at once.
A) O(log n) or O(n) B) O(m log m) or O(m2) C) O(n log n) or O(n + m log n) D) O(m log n) or O(m + n log n)
A) O(m + n log n) B) O(m log n (log log n)3) C) O(m log n) D) O(n log n)
A) Backtracking algorithms B) Divide and conquer algorithms C) Dynamic programming algorithms D) Greedy algorithms
A) NP B) FP C) P-space D) Exponential time
A) No B) Only for small graphs C) Only for trees D) Yes
A) Binary search tree B) Disjoint set union C) Soft heap D) Fibonacci heap
A) Exactly 1 B) Infinity C) Exactly 10 D) No greater than 4
A) log r B) r2 C) r4 D) r
A) r! B) r2 C) 2r D) 2r2
A) Seth Pettie and Vijaya Ramachandran B) Alan M. Frieze and Svante Janson C) Vijaya Ramachandran and Svante Janson D) J. Michael Steele and Seth Pettie
A) The entire graph structure B) Only its own connected links C) The total weight of the global MST D) The coordinates of all other nodes
A) J. Michael Steele B) Alan M. Frieze C) Svante Janson D) Seth Pettie
A) The ellipsoid method B) Backtracking C) Greedy algorithm D) Dynamic programming
A) NP-hard B) Logarithmic time C) Polynomial time D) Linear time
A) Hamiltonian cycle problem B) Maximum flow problem C) Shortest path problem D) Bipartite matching problem
A) O(V log V) B) NP-hard C) P D) NP-complete
A) Euclidean distance B) Manhattan distance C) Rectilinear distance D) Chebyshev distance |