• Sepehr Hajebi, Holes, hubs and bounded treewidth

    Zoom ID: 869 4632 6610 (ibsdimag)

    A hole in a graph $G$ is an induced cycle of length at least four, and for every hole $H$ in $G$, a vertex $h\in G\setminus H$ is called a $t$-hub for $H$ if $h$ has at least $t$ neighbor in $H$. Sintiari and Trotignon were the first to construct graphs with arbitrarily large treewidth

  • Kevin Hendrey, Product Structure of Graph Classes with Bounded Treewidth

    Room B232 IBS (기초과학연구원)

    The strong product $G\boxtimes H$ of graphs $G$ and $H$ is the graph on the cartesian product $V(G)\times V(H)$ such that vertices $(v,w)$ and $(x,y)$ are adjacent if and only if $\max\{d_G(v,x),d_H(w,y)\}=1$. Graph product structure theory aims to describe complicated graphs in terms of subgraphs of strong products of simpler graphs. This area of research was initiated

  • Jinyoung Park (박진영), Thresholds 1/2

    Room B332 IBS (기초과학연구원)

    Thresholds for increasing properties of random structures are a central concern in probabilistic combinatorics and related areas. In 2006, Kahn and Kalai conjectured that for any nontrivial increasing property on a finite set, its threshold is never far from its "expectation-threshold," which is a natural (and often easy to calculate) lower bound on the threshold.

  • Jinyoung Park (박진영), Thresholds 2/2

    Room B332 IBS (기초과학연구원)

    Thresholds for increasing properties of random structures are a central concern in probabilistic combinatorics and related areas. In 2006, Kahn and Kalai conjectured that for any nontrivial increasing property on a finite set, its threshold is never far from its "expectation-threshold," which is a natural (and often easy to calculate) lower bound on the threshold.

  • Noam Lifshitz, Product free sets in the alternating group

    Zoom ID: 870 0312 9412 (ibsecopro) [CLOSED]

    A subset of a group is said to be product free if it does not contain the product of two elements in it. We consider how large can a product free subset of $A_n$ be? In the talk we will completely solve the problem by determining the largest product free subset of $A_n$. Our proof

  • Seunghun Lee (이승훈), Inscribable order types

    Room B332 IBS (기초과학연구원)

    We call an order type inscribable if it is realized by a point configuration where all extreme points are all on a circle. In this talk, we investigate inscribability of order types. We first show that every simple order type with at most 2 interior points is inscribable, and that the number of such order

  • Lars Jaffke, Taming graphs with no large creatures and skinny ladders

    Zoom ID: 869 4632 6610 (ibsdimag)

    We confirm a conjecture of Gartland and Lokshtanov : if for a hereditary graph class $\mathcal{G}$ there exists a constant $k$ such that no member of $\mathcal{G}$ contains a $k$-creature as an induced subgraph or a $k$-skinny-ladder as an induced minor, then there exists a polynomial $p$ such that every $G \in \mathcal{G}$ contains at

  • Eun Jung Kim (김은정), Directed flow-augmentation

    Room B332 IBS (기초과학연구원)

    We show a flow-augmentation algorithm in directed graphs: There exists a polynomial-time algorithm that, given a directed graph G, two integers $s,t\in V(G)$, and an integer $k$, adds (randomly) to $G$ a number of arcs such that for every minimal st-cut $Z$ in $G$ of size at most $k$, with probability $2^{−\operatorname{poly}(k)}$ the set $Z$

  • Akash Kumar, Random walks and Forbidden Minors

    Zoom ID: 870 0312 9412 (ibsecopro) [CLOSED]

    Random walks and spectral methods have had a strong influence on modern graph algorithms as evidenced by the extensive literature on the subject. In this talk, I will present how random walks helped make progress on algorithmic problems on planar graphs. In particular, I show how random walk based (i.e., spectral) approaches led to progress

  • Noleen Köhler, Testing first-order definable properties on bounded degree graphs

    Room B332 IBS (기초과학연구원)

    Property testers are probabilistic algorithms aiming to solve a decision problem efficiently in the context of big-data. A property tester for a property P has to decide (with high probability correctly) whether a given input graph has property P or is far from having property P while having local access to the graph. We study