human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "on the hardest problem formulations for the 0 1 lasserre hierarchy"
  Abstract: The Lasserre/Sum-of-Squares (SoS) hierarchy is a systematic procedure for constructing a sequence of increasingly tight semidefinite relaxations. It is known that the hierarchy converges to the 0/1 polytope in n levels and captures the convex relaxations used in the best available approximation algorithms for a wide variety of optimization problems. #R##N#In this paper we characterize the set of 0/1 integer linear problems and unconstrained 0/1 polynomial optimization problems that can still have an integrality gap at level n-1. These problems are the hardest for the Lasserre hierarchy in this sense.

Connected through hyperedge HE-1 (induced by source paper "breaking symmetries to rescue sum of squares the case of makespan scheduling"):
  with members:
    - "proximity results and faster algorithms for integer programming using the steinitz lemma"
    - "the power of sum of squares for detecting hidden structures"
    - "sum of squares lower bounds for refuting any csp"
    - "quasi ptas for scheduling with precedences using lp hierarchies"
    - "a nearly tight sum of squares lower bound for the planted clique problem"
    - "polynomial time tensor decompositions with sum of squares"
    - "closing the gap for makespan scheduling via sparsification techniques"
    - "a 1 epsilon approximation for makespan scheduling with precedence constraints using lp hierarchies"

Connected through hyperedge HE-2 (induced by source paper "optimization over the boolean hypercube via sums of nonnegative circuit polynomials"):
  with members:
    - "on the bit complexity of sum of squares proofs"
    - "a nearly tight sum of squares lower bound for the planted clique problem"
    - "sum of squares lower bounds for planted clique"
    - "lower bounds on the size of semidefinite programming relaxations"
    - "sum of squares hierarchy lower bounds for symmetric formulations"
    - "sum of squares proofs and the quest toward optimal algorithms"
    - "approximating csps with global cardinality constraints using sdp hierarchies"

Connected through hyperedge HE-3 (induced by source paper "on bounded pitch inequalities for the min knapsack polytope"):
  with members:
    - "small extended formulation for knapsack cover inequalities from monotone circuits"

Connected through hyperedge HE-4 (induced by source paper "tight sum of squares lower bounds for binary polynomial optimization problems"):
  with members:
    - "on the sum of squares degree of symmetric quadratic functions"
    - "sum of squares lower bounds for planted clique"
    - "lower bounds on the size of semidefinite programming relaxations"
    - "hypercontractivity sum of squares proofs and their applications"

Connected through hyperedge HE-5 (induced by source paper "a lasserre lower bound for the min sum single machine scheduling problem"):
  with members:
    - "sum of squares lower bounds from pairwise independence"
    - "sum of squares lower bounds for planted clique"
    - "a 4 approximation for scheduling on a single machine with general cost function"
    - "approximability and proof complexity"
    - "polynomial integrality gaps for strong sdp relaxations of densest k subgraph"
    - "integrality gaps of linear and semi definite programming relaxations for knapsack"
    - "the geometry of scheduling"

Connected through hyperedge HE-6 (induced by source paper "sum of squares hierarchy lower bounds for symmetric formulations"):
  with members:
    - "tight sum of squares lower bounds for binary polynomial optimization problems"
    - "on the sum of squares degree of symmetric quadratic functions"
    - "a lasserre lower bound for the min sum single machine scheduling problem"
    - "sum of squares lower bounds from pairwise independence"
    - "sum of squares lower bounds for planted clique"
    - "a 4 approximation for scheduling on a single machine with general cost function"
    - "lower bounds on the size of semidefinite programming relaxations"
    - "sum of squares proofs and the quest toward optimal algorithms"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CC(Computational Complexity)