Introduction to algorithms [2nd ed.]

By T. Cormen. 2001

2,622 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d32371bda0cc6012376b1a55b6852a8338855e40

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Citations in the corpus

Secure and practical outsourcing of linear programming in cloud computing (2011, unknown): “(See Lemma 29.11 in [17]).”
A Survey of Evolutionary Algorithms for Clustering (2009, background): “These elements represent the (N−1) edges of a minimum spanning tree (MST) [24] in which the”
Approximated and User Steerable tSNE for Progressive Visual Analytics (2015, methodology): “Therefore, a breadth-ﬁrst visit [43] of the graph created by the KNN relationships can be used to extend the reﬁnement.”
Team Cornell's Skynet: Robust perception and planning in an urban environment (2008, methodology): “An obstacle processing loop first transforms obstacle point clouds into polygonal obstacles using a convex hull algorithm (Cormen et al., 2003).”
Early exit optimizations for additive machine learned ranking systems (2010, unknown): “Algorithm 3 shows an ecient version which uses the linear-time selection algorithm [ 10 ] (SELECT) for finding the document at rank rt[p] (instead of sorting the documents) and prunes the documents based on this pivot document’s score.”
Pursuit-Evasion on Trees by Robot Teams (2010, background): “It is assumed that the reader is familiar with graphs and trees, and is referred to [ 33 ] for the basic notation and terminology that we use.”
Handbook of Big Data (2016, background): “…recognizably larger than the upper (the reader may have to zoom in while viewing the ﬁgure in a PDF reader), implying that the correlation of age at ados.. with both ..vma.. and ..nvma.. is positive, but more strongly with the former than the latter, which may be news to the nonspecialist: verbal”
Approximate distance oracles (2001, methodology): “This takes O(m + n log n) time using the classical algorithm of Dijkstra [1959], implemented using Fibonacci heaps [Fredman and Tarjan 1987] (see also Cormen et al.”
Legislative cosponsorship networks in the US House and Senate (2006, methodology): “Dijkstra’s algorithm (Cormen et al., 2001) then allows us to find the shortest distance between each pair of legislators using the following steps: (1) Starting with legislator j, identify from a list of all other legislators the closest legislator i.”
Planning algorithms (2006, methodology): “Samples can be gradually added, and the connectivity can be updated efficiently using the union-find algorithm [245, 826].”