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  1. 30. Mai 2024 · As one of the fundamental matrix operations, the sparse matrix chain multiplication (SMCM) aims to efficiently multiply a chain of sparse matrices, which has found various real-world applications in areas like network analysis, data mining, and machine learning.

  2. Vor 6 Tagen · Ronald L. Rivest, Adi Shamir und Leonard Adleman versuchten eigentlich zu beweisen, dass es ebensolche Falltürfunktionen nicht geben kann. Bei den Beweisversuchen stießen sie jedoch tatsächlich auf eine solche Einwegfunktion mit Falltür. Das führte 1977 zur Entwicklung des berühmtesten Public-Key-Algorithmus, des nach den ...

  3. 18. Mai 2024 · Introduction to Algorithms combines the attributes of comprehensiveness and comprehensibility. It will be equally useful as a text, a handbook, and a general reference. Introduction to Algorithms covers both classical material and such modern developments as amortized analysis and parallel algorithms.

  4. datatracker.ietf.org › doc › htmldraft-rivest-sexp-09

    24. Mai 2024 · Introduction. This memo specifies a data structure representation that is suitable for representing arbitrary, complex data structures. It was devised in 1996/1997 to support SPKI [ RFC2692] certificates with the intent that it be more widely applicable (see Section 1.3, History).

  5. 30. Mai 2024 · Effective resistance (ER) is a fundamental metric for measuring node similarities in a graph, and it finds applications in various domains including graph clustering, recommendation systems, link prediction, and graph neural networks.

  6. 30. Mai 2024 · ABSTRACT. Neural networks have achieved remarkable empirical performance, while the current theoretical analysis is not adequate for understanding their success, e.g., the Neural Tangent Kernel approach fails to capture their key feature learning ability, while recent analyses on feature learning are typically problem-specific.

  7. ioinformatics.org › page › recommended-readingRecommended Reading

    26. Mai 2024 · Thomas H. Cormen, Charles E. Leiserson, and Ronald L. Rivest, Clifford Stein. The MIT Press / McGraw-Hill, 2001. An excellent overview of practical algorithms and their design is: