A remark on the problem of nonnegative k-subset sums

Given a set of n real numbers with a nonnegative sum, consider the family of all its k-element subsets with nonnegative sums. How small can the size of this family be? We show that this problem is closely related to a problem raised by Ahlswede and Khachatrian in [1]. The latter, in a special case, is nothing else but the problem of determining a minimal number c _n (k) such that any k-uniform hypergraph on n vertices having c _n (k) + 1 edges has a perfect fractional matching. We show that results obtained in [1] can be applied for the former problem. Moreover, we conjecture that these problems have in general the same solution.     

Some results on graphs without long induced paths

Many NP-hard graph problems remain difficult on P_k-free graphs for certain values of k. Our goal is to distinguish subclasses of P_k-free graphs where several important graph problems can be solved in polynomial time. In particular, we show that the independent set problem is polynomial-time solvable in the class of (P_k,K_1,n)-free graphs for any positive integers k and n, thereby generalizing several known results.     

Strong computational lower bounds via parameterized complexity

We develop new techniques for deriving strong computational lower bounds for a class of well-known NP-hard problems. This class includes weighted satisfiability, dominating set, hitting set, set cover, clique, and independent set. For example, although a trivial enumeration can easily test in time O(nk) if a given graph of n vertices has a clique of size k, we prove that unless an unlikely collapse occurs in parameterized complexity theory, the problem is not solvable in time f(k)no(k) for any function f, even if we restrict the parameter values to be bounded by an arbitrarily small function of n. Under the same assumption, we prove that even if we restrict the parameter values k to be of the order Θ(μ(n)) for any reasonable function μ, no algorithm of running time no(k) can test if a graph of n vertices has a clique of size k. Similar strong lower bounds on the computational complexity are also derived for other NP-hard problems in the above class. Our techniques can be further extended to derive computational lower bounds on polynomial time approximation schemes for NP-hard optimization problems. For example, we prove that the NP-hard distinguishing substring selection problem, for which a polynomial time approximation scheme has been recently developed, has no polynomial time approximation schemes of running time f(1/?)no(1/?) for any function f unless an unlikely collapse occurs in parameterized complexity theory.     

Online coloring of hypergraphs

We give a tight bound on randomized online coloring of hypergraphs. The bound holds even if the algorithm knows the hypergraph in advance (but not the ordering in which it is presented). More specifically, we show that for any n and k, there is a 2-colorable k-uniform hypergraph on n vertices for which any randomized online coloring uses Ω(n/k) colors in expectation.     

Hadamard tensors and lower bounds on multiparty communication complexity

We develop a new method for estimating the discrepancy of tensors associated with multiparty communication problems in the “Number on the Forehead” model of Chandra, Furst, and Lipton. We define an analog of the Hadamard property of matrices for tensors in multiple dimensions and show that any k-party communication problem represented by a Hadamard tensor must have Ω(n/2 ^k ) multiparty communication complexity. We also exhibit constructions of Hadamard tensors. This allows us to obtain Ω(n/2 ^k ) lower bounds on multiparty communication complexity for a new class of explicitly defined Boolean functions.     

Boolean-width of graphs

We introduce the graph parameter boolean-width, related to the number of different unions of neighborhoods-Boolean sums of neighborhoods-across a cut of a graph. For many graph problems, this number is the runtime bottleneck when using a divide-and-conquer approach. For an n-vertex graph given with a decomposition tree of boolean-width k, we solve Maximum Weight Independent Set in time O(n²k2^2k) and Minimum Weight Dominating Set in time O(n²+nk2^3k). With an additional n² factor in the runtime, we can also count all independent sets and dominating sets of each cardinality.Boolean-width is bounded on the same classes of graphs as clique-width. boolean-width is similar to rank-width, which is related to the number of GF(2)-sums of neighborhoods instead of the Boolean sums used for boolean-width. We show for any graph that its boolean-width is at most its clique-width and at most quadratic in its rank-width. We exhibit a class of graphs, the Hsu-grids, having the property that a Hsu-grid on Θ(n²) vertices has boolean-width Θ(logn) and rank-width, clique-width, tree-width, and branch-width Θ(n).     

Optimal per-edge processing times in the semi-streaming model

We present semi-streaming algorithms for basic graph problems that have optimal per-edge processing times and therefore surpass all previous semi-streaming algorithms for these tasks. The semi-streaming model, which is appropriate when dealing with massive graphs, forbids random access to the input and restricts the memory to bits.Particularly, the formerly best per-edge processing times for finding the connected components and a bipartition are O(α(n)), for determining k-vertex and k-edge connectivity O(k²n) and O(n⋅logn) respectively for any constant k and for computing a minimum spanning forest O(logn). All these time bounds we reduce to O(1).Every presented algorithm determines a solution asymptotically as fast as the best corresponding algorithm up to date in the classical RAM model, which therefore cannot convert the advantage of unlimited memory and random access into superior computing times for these problems.     

Almost k-wise independence versus k-wise independence

We say that a distribution over {0,1}ⁿ is (ε,k)-wise independent if its restriction to every k coordinates results in a distribution that is ε-close to the uniform distribution. A natural question regarding (ε,k)-wise independent distributions is how close they are to some k-wise independent distribution. We show that there exist (ε,k)-wise independent distributions whose statistical distance is at least n^O(k)·ε from any k-wise independent distribution. In addition, we show that for any (ε,k)-wise independent distribution there exists some k-wise independent distribution, whose statistical distance is n^O(k)·ε.     

Unbalanced Graph Partitioning

We investigate the unbalanced cut problems. A cut (A,B) is called unbalanced if the size of its smaller side is at most k (called k-size) or exactly k (called Ek-size), where k is an input parameter. We consider two closely related unbalanced cut problems, in which the quality of a cut is measured with respect to the sparsity and the conductance, respectively. We show that even if the input graph is restricted to be a tree, the Ek-Sparsest Cut problem (to find an Ek-size cut with the minimum sparsity) is still NP-hard. We give a bicriteria approximation algorithm for the k-Sparsest Cut problem (to find a k-size cut with the minimum sparsity), which outputs a cut whose sparsity is at most O(logn) times the optimum and whose smaller side has size at most O(logn)k. As a consequence, this leads to a (O(logn),O(logn))-bicriteria approximation algorithm for the Min k-Conductance problem (to find a k-size cut with the minimum conductance).