KAIST Discrete Math Seminar


Seminar series on discrete mathematics @ Dept. of Mathematical Sciences, KAIST.
  • Xin Zhang, On equitable tree-colorings of graphs

    IBS/KAIST Joint Discrete Math Seminar

    On equitable tree-colorings of graphs
    Xin Zhang (张欣)
    Xidian Univeristy, China
    2019/05/16 4:30PM-5:30PM (IBS, B232)
    An equitable tree-k-coloring of a graph is a vertex coloring using k distinct colors such that every color class (i.e, the set of vertices in a common color) induces a forest and the sizes of any two color classes differ by at most one. The minimum integer k such that a graph G is equitably tree-k-colorable is the equitable vertex arboricity of G, denoted by vaeq(G). A graph that is equitably tree-k-colorable may admits no equitable tree-k′-coloring for some k′>k. For example, the complete bipartite graph K9,9 has an equitable tree-2-coloring but is not equitably tree-3-colorable. In view of this a new chromatic parameter so-called the equitable vertex arborable threshold is introduced. Precisely, it is the minimum integer k such that G has an equitable tree-k′-coloring for any integer k′≥k, and is denoted by vaeq(G). The concepts of the equitable vertex arboricity and the equitable vertex arborable threshold were introduced by J.-L. Wu, X. Zhang and H. Li in 2013. In 2016, X. Zhang also introduced the list analogue of the equitable tree-k-coloring. There are many interesting conjectures on the equitable (list) tree-colorings, one of which, for example, conjectures that every graph with maximum degree at most Δ is equitably tree-k-colorable for any integer k≥(Δ+1)/2, i.e, vaeq(G)≤⌈(Δ+1)/2⌉. In this talk, I review the recent progresses on the studies of the equitable tree-colorings from theoretical results to practical algorithms, and also share some interesting problems for further research.
  • Sang June Lee (이상준), On strong Sidon sets of integers

    IBS/KAIST Joint Discrete Math Seminar

    On strong Sidon sets of integers
    Sang June Lee
    Duksung Women’s University, Seoul
    2019/05/08 Wed 4:30PM-5:30PM (IBS, Room B232)
    Let N be the set of natural numbers. A set A⊂N is called a Sidon set if the sums a1+a2, with a1,a2∈S and a1≤a2, are distinct, or equivalently, if
    |(x+w)−(y+z)|≥1
    for every x,y,z,w∈S with x<y≤z<w. We define strong Sidon sets as follows:</p>

    For a constant α with 0≤α<1, a set S⊂N is called an α-strong Sidon set if
    |(x+w)−(y+z)|≥wα
    for every x,y,z,w∈S with x<y≤z<w.

    The motivation of strong Sidon sets is that a strong Sidon set generates many Sidon sets by altering each element a bit. This infers that a dense strong Sidon set will guarantee a dense Sidon set contained in a sparse random subset of N.

    In this talk, we are interested in how dense a strong Sidon set can be. This is joint work with Yoshiharu Kohayakawa, Carlos Gustavo Moreira and Vojtěch Rödl.

  • Rose McCarty, Circle graphs are polynomially chi-bounded

    IBS/KAIST Joint Discrete Math Seminar

    Circle graphs are polynomially chi-bounded
    Rose McCarty
    University of Waterloo, Waterloo, Canada
    2019/04/26 Fri 4PM-5PM (IBS, Room B232)
    Circle graphs are the intersection graphs of chords on a circle; vertices correspond to chords, and two vertices are adjacent if their chords intersect. We prove that every circle graph with clique number k has chromatic number at most 4k2. Joint with James Davies.
    Tags:
  • Jon-Lark Kim (김종락), Introduction to Boolean functions with Artificial Neural Network

    IBS/KAIST Joint Discrete Math Seminar

    Introduction to Boolean functions with Artificial Neural Network
    Jon-Lark Kim (김종락)
    Department of Mathematics, Sogang University, Seoul
    2019/04/18 Thu 11:00AM-12:00PM (IBS, Room B232)
    A Boolean function is a function from the set Q of binary vectors of length n (i.e., the binary n-dimensional hypercube) to F2={0,1}. It has several applications to complexity theory, digital circuits, coding theory, and cryptography.In this talk we give a connection between Boolean functions and Artificial Neural Network. We describe how to represent Boolean functions by Artificial Neural Network including linear and polynomial threshold units and sigmoid units. For example, even though a linear threshold function cannot realize XOR, a polynomial threshold function can do it. We also give currently open problems related to the number of (Boolean) linear threshold functions and polynomial threshold functions.
  • Andreas Holmsen, Large cliques in hypergraphs with forbidden substructures

    IBS/KAIST Joint Discrete Math Seminar

    Large cliques in hypergraphs with forbidden substructures
    Andreas Holmsen
    Department of Mathematical Sciences, KAIST
    2019/03/12 Tue 4:30PM-5:30PM (Room B232, IBS)
    A result due to Gyárfás, Hubenko, and Solymosi, answering a question of Erdős, asserts that if a graph G does not contain K2,2 as an induced subgraph yet has at least c n(n-1)/2 edges, then G has a complete subgraph on at least c^2 n /10 vertices. In this paper we suggest a “higher-dimensional” analogue of the notion of an induced K2,2, which allows us to extend their result to k-uniform hypergraphs. Our result also has interesting consequences in topological combinatorics and abstract convexity, where it can be used to answer questions by Bukh, Kalai, and several others.

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