Although this may seem a paradox, all exact science is dominated by the idea of approximation. Bertrand Russell (1872-1970) Most natural optimization problems, including those arising in important application areas, are NP-hard. Therefore, under the widely believed con jecture that P -=/= NP, their exact solution is prohibitively time consuming. Charting the landscape of approximability of these problems, via polynomial time algorithms, therefore becomes a compelling subject of scientific inquiry in computer science and mathematics. This book presents the theory of ap proximation algorithms as it stands today. It is reasonable to expect the picture to change with time. This book is divided into three parts. In Part I we cover combinato rial algorithms for a number of important problems, using a wide variety of algorithm design techniques. The latter may give Part I a non-cohesive appearance. However, this is to be expected - nature is very rich, and we cannot expect a few tricks to help solve the diverse collection of NP-hard problems. Indeed, in this part, we have purposely refrained from tightly cat egorizing algorithmic techniques so as not to trivialize matters. Instead, we have attempted to capture, as accurately as possible, the individual character of each problem, and point out connections between problems and algorithms for solving them.
SPOKEN ENGLISH WITH BENGALI KNOW THE MEANING OF BENGALI AND SPEAK ENGLISH. BENGALI TO ENGLISH DICTIONARY, SPOKEN BOOK,
This article was first published in October 2017.
Whether you are building Machine Learning models or making decisions in everyday life, we always choose the path with the least amount of risk. As humans, we are hardwired to take any action that…
With special t.-p.: ... The T'sing wan k'e mung; or, Manchu preceptor, translated from the Chinese, by A. Wylie
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Chomsky proposes a reformulation of the theory of transformational generative grammar that takes recent developments in the descriptive analysis of particula...
M. Payre, Les Rêves et la Vie CM1-CM2, 8e-7e, Librairie classique Eugène Belin, 1967. Textes choisis. Illustrations de Paul Durand. Cliquez sur une des images pour lancer le diaporama. Plus petites images, voir ici.
Deep Learning is amazing. But why is Deep Learning so successful? Is Deep Learning just old-school Neural Networks on modern hardware? Is it just that we have so much data now the methods work b…