Deciding Monotone Duality and Identifying Frequent Itemsets in Quadratic Logspace
원문 초록
The monotone duality problem is defined as follows: Given two monotone formulas f and g in iredundant DNF, decide whether f and g are dual. This problem is the same as duality testing for hypergraphs, that is, checking whether a hypergraph H consists of precisely all minimal transversals of a simple hypergraph G. By exploiting a recent problem-decomposition method by Boros and Makino (ICALP 2009), we show that duality testing for hypergraphs, and thus for monotone DNFs, is feasible in DSPACE[log^2 n], i.e., in quadratic logspace. As the monotone duality problem is equivalent to a number of problems in the areas of databases, data mining, and knowledge discovery, the results presented here yield new complexity results for those problems, too. For example, it follows from our results that whenever for a Boolean-valued relation (whose attributes represent items), a number of maximal frequent itemsets and a number of minimal infrequent itemsets are known, then it can be decided in quadratic logspace whether there exist additional frequent or infrequent itemsets.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need
RAISE: Enhancing Scientific Reasoning in LLMs via Step-by-Step Retrieval
TableTime: Reformulating Time Series Classification as Zero-Shot Table Understanding via Large Language Models
SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation
SparseLLM: Towards Global Pruning for Pre-trained Language Models
Divide-or-Conquer? Which Part Should You Distill Your LLM?
토론
이 논문과 연결된 포럼 글이 아직 없습니다.