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: "the backtracking survey propagation algorithm for solving random k sat problems"
  Abstract: The K-satisfability problem is a combinatorial discrete optimization problem, which for K=3 is NP-complete, and whose random formulation is of interest for understanding computational complexity. Here, the authors introduce the backtracking survey propagation algorithm for studying it for K=3 and K=4.

Connected through hyperedge HE-1 (induced by source paper "the sdp value for random two eigenvalue csps"):
  with members:
    - "the threshold for sdp refutation of random regular nae 3sat"
    - "the lov asz theta function for random regular graphs and community detection in the hard regime"
    - "sum of squares lower bounds for refuting any csp"
    - "strongly refuting random csps below the spectral threshold"
    - "semidefinite programs on sparse random graphs and their application to community detection"
    - "a composition theorem for parity kill number"
    - "spectral redemption in clustering sparse networks"
    - "community detection thresholds and the weak ramanujan property"

Connected through hyperedge HE-2 (induced by source paper "problem solving at the edge of chaos entropy puzzles and the sudoku freezing transition"):
  with members:
    - "combining the k cnf and xor phase transitions"
    - "computational red teaming in a sudoku solving context neural network based skill representation and acquisition"
    - "the condensation phase transition in random graph coloring"
    - "difficulty rating of sudoku puzzles an overview and evaluation"
    - "aspects of statistical physics in computational complexity"
    - "on the role of working memory in trading off skills and situation awareness in sudoku"
    - "there is no 16 clue sudoku solving the sudoku minimum number of clues problem"
    - "view based propagator derivation"

Connected through hyperedge HE-3 (induced by source paper "streamlining variational inference for constraint satisfaction problems"):
  with members:
    - "adversarial constraint learning for structured prediction"
    - "label free supervision of neural networks with physics and domain knowledge"
    - "closing the gap between short and long xors for model counting"
    - "a new look at survey propagation and its generalizations"
    - "survey propagation an algorithm for satisfiability"

Connected through hyperedge HE-4 (induced by source paper "constructing concrete hard instances of the maximum independent set problem"):
  with members:
    - "on independent sets in random graphs"
    - "from average case complexity to improper learning complexity"
    - "average case complexity"
    - "generating hard satisfiable formulas by hiding solutions deceptively"

Connected through hyperedge HE-5 (induced by source paper "sum of squares lower bounds for refuting any csp"):
  with members:
    - "lower bounds for csp refutation by sdp hierarchies"
    - "strongly refuting random csps below the spectral threshold"
    - "how to refute a random csp"
    - "noisy tensor completion via the sum of squares hierarchy"
    - "complexity theoretic limitations on learning halfspaces"
    - "sum of squares lower bounds from pairwise independence"
    - "lower bounds on the size of semidefinite programming relaxations"
    - "hardness of robust graph isomorphism lasserre gaps and asymmetry of random graphs"

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)