• StdPooling-PolyAlgos

  • Referenced in 5 articles [sw34823]
  • from sparse strongly-polynomial solutions to NP-hardness. The standard pooling problem ... NP-hard subclass of non-convex quadratically-constrained optimization problems that commonly arises in process...
  • Cross

  • Referenced in 7 articles [sw30282]
  • implementation of some previous methods are NP-hard. In this article, we propose a framework...
  • Quartets MaxCut

  • Referenced in 7 articles [sw29616]
  • quartet trees the problem is NP-hard, as opposed to the problem for triples where...
  • Rec-I-DCM3

  • Referenced in 6 articles [sw29614]
  • Phylogenetic trees are commonly reconstructed based on hard optimization problems such as maximum parsimony ... since MP (and presumably ML) is NP-hard, such approaches do not scale when applied...
  • V-MDAV

  • Referenced in 6 articles [sw11787]
  • sets is known to be difficult (NP-hard). Therefore, heuristic methods are used in practice...
  • ADMBB

  • Referenced in 5 articles [sw31752]
  • applications and is known to be NP-hard even with one negative eigenvalue (QP1NE...
  • NeMa

  • Referenced in 5 articles [sw18899]
  • show that the problem is NP-hard, and also hard to approximate. (3) We propose...
  • GASTS

  • Referenced in 5 articles [sw29624]
  • these rearrangements. However, rearrangements lead to NP-hard problems, so that current approaches, such...
  • ToTo

  • Referenced in 3 articles [sw19369]
  • retrieval of tree decompositions. Many NP-hard problems on graphs become tractable on graphs ... Unfortunately computation of treewidth is itself NP-hard and a wide variety of exact, heuristic...
  • CoReS

  • Referenced in 4 articles [sw28116]
  • problem of finding its core is NP-hard. Using the Tool {it CoReS}, we automatically...
  • ParSSSE

  • Referenced in 4 articles [sw17623]
  • literature. Solving such problems is generally NP-hard, so that a brute-force approach...
  • FastRFS

  • Referenced in 2 articles [sw29617]
  • analyses, but maximum likelihood approaches are NP-hard and Bayesian MCMC methods do not scale ... heterogeneous datasets. Supertree estimation is itself NP-hard, and no current supertree method has sufficient...
  • k-Neighborhood

  • Referenced in 3 articles [sw13966]
  • limited memory) influence diagram is an NP-hard problem, often approached through local search...
  • VOROPACK-D

  • Referenced in 3 articles [sw40483]
  • circular container. DPP is known NP-hard and reported algorithms are slow for finding good...
  • GlobalMIT

  • Referenced in 3 articles [sw38463]
  • regulatory network (GRN). Due to the NP-hard nature of learning static Bayesian network structure...
  • Grid BnB

  • Referenced in 3 articles [sw12931]
  • optimal solutions of search problems and NP-hard optimization problems. Grid’BnB is a Java...
  • TFRP

  • Referenced in 3 articles [sw37089]
  • minimum information loss is an NP-hard problem. Existing fixed-size techniques can obtain...
  • BetaSCP

  • Referenced in 3 articles [sw08772]
  • side-chain positioning problem is NP-hard. On the other hand, popular heuristic approaches focusing...