Number partitioning | Matroid theory
Matroid-constrained number partitioning is a variant of the multiway number partitioning problem, in which the subsets in the partition should be independent sets of a matroid. The input to this problem is a set S of items, a positive integer m, and some m matroids over the same set S. The goal is to partition S into m subsets, such that each subset i is an independent set in matroid i. Subject to this constraint, some objective function should be minimized, for example, minimizing the largest sum item sizes in a subset. In a more general variant, each of the m matroids has a weight function, which assigns a weight to each element of the ground-set. Various objective functions have been considered. For each of the three operators max,min,sum, one can use this operator on the weights of items in each subset, and on the subsets themselves. All in all, there are 9 possible objective functions, each of which can be maximized or minimized. (Wikipedia).
James Oxley: A matroid extension result
Abstract: Let (A,B) be a 3-separation in a matroid M. If M is representable, then, in the underlying projective space, there is a line where the subspaces spanned by A and B meet, and M can be extended by adding elements from this line. In general, Geelen, Gerards, and Whittle proved that
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Yusuke Kobayashi: A weighted linear matroid parity algorithm
The lecture was held within the framework of the follow-up workshop to the Hausdorff Trimester Program: Combinatorial Optimization. Abstract: The matroid parity (or matroid matching) problem, introduced as a common generalization of matching and matroid intersection problems, is so gener
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Limit shapes and their analytic parameterizations – Richard Kenyon – ICM2018
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Steffen Borgwardt: The role of partition polytopes in data analysis
The field of optimization, and polyhedral theory in particular, provides a powerful point of view on common tasks in data analysis. In this talk, we highlight the role of the so-called partition polytopes and their studies in clustering and classification. The geometric properties of parti
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Gyula Pap: Linear matroid matching in the oracle model
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From playlist HIM Lectures 2015
Yuval Filmus: Monotone Submodular Optimization over a Matroid
We consider the NP-hard problem of maximizing a monotone submodular function over a matroid constraint. Vondrak's continuous greedy algorithm achieves the best possible approximation ratio 1-1/e using continuous methods. Can the same be accomplished combinatorially? We show that this is ar
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Clustering is the process of grouping a set of data given a certain criterion. In this way it is possible to define subgroups of data, called clusters, that share common characteristics. Determining the internal structure of the data is important in exploratory data analysis, but is also u
From playlist “How To” with MATLAB and Simulink
Nonlinear algebra, Lecture 13: "Polytopes and Matroids ", by Mateusz Michalek
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Jesus De Loera: Tverberg-type theorems with altered nerves
Abstract: The classical Tverberg's theorem says that a set with sufficiently many points in R^d can always be partitioned into m parts so that the (m - 1)-simplex is the (nerve) intersection pattern of the convex hulls of the parts. Our main results demonstrate that Tverberg's theorem is b
From playlist Combinatorics
Mathematica Tutorial 20 - Limits of Functions and Sequences
In this Mathematica tutorial you will learn about limits of functions and sequences. *** SUBSCRIBE FOR MORE VIDEOS *** Never miss a daily video about Mathematics and Mathematica. Subscribe: https://www.youtube.com/channel/UCbqxG8H7jg-I0XAMzUdS1Xw?sub_confirmation=1
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Lauren Williams - Combinatorics of the amplituhedron
The amplituhedron is the image of the positive Grassmannian under a map in- duced by a totally positive matrix. It was introduced by Arkani-Hamed and Trnka to compute scattering amplitudes in N=4 super Yang Mills. I’ll give a gentle introduction to the amplituhedron, surveying its connecti
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András Frank: Non TDI Optimization with Supermodular Functions
The notion of total dual integrality proved decisive in combinatorial optimization since it properly captured a phenomenon behind the tractability of weighted optimization problems. For example, we are able to solve not only the maximum cardinality matching (degree-constrained subdigraph,
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Network Analysis. Lecture 9. Graph partitioning algorithms
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Nexus Trimester - František Matúš (Institute of Information Theory and Automation) 2/3
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Kevin Hendrey - Obstructions to bounded branch-depth in matroids (CMSA Combinatorics Seminar)
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A video segment from the Coursera MOOC on introductory computer programming with MATLAB by Vanderbilt. Lead instructor: Mike Fitzpatrick. Check out the companion website and textbook: http://cs103.net
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