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 szk and pp"
  Abstract: In both query and communication complexity, we give separations between the class NISZK, containing those problems with non-interactive statistical zero knowledge proof systems, and the class UPP, containing those problems with randomized algorithms with unbounded error. These results significantly improve on earlier query separations of Vereschagin [Ver95] and Aaronson [Aar12] and earlier communication complexity separations of Klauck [Kla11] and Razborov and Sherstov [RS10]. In addition, our results imply an oracle relative to which the class NISZK is not contained in PP. This answers an open question of Watrous from 2002 [Aar]. The technical core of our result is a stronger hardness amplification theorem for approximate degree, which roughly says that composing the gapped-majority function with any function of high approximate degree yields a function with high threshold degree. Using our techniques, we also give oracles relative to which the following two separations hold: perfect zero knowledge (PZK) is not contained in its complement (coPZK), and SZK (indeed, even NISZK) is not contained in PZK (indeed, even HVPZK). Along the way, we show that HVPZK is contained in PP in a relativizing manner. #R##N#We prove a number of implications of these results, which may be of independent interest outside of structural complexity. Specifically, our oracle separation implies that certain parameters of the Polarization Lemma of Sahai and Vadhan [SV03] cannot be much improved in a black-box manner. Additionally, it implies new lower bounds for property testing algorithms with error probability arbitrarily close to 1/2. Finally, our results imply that two-message protocols in the streaming interactive proofs model of Cormode et al. [CTY11] are surprisingly powerful in the sense that, with just logarithmic cost, they can compute functions outside of UPP^CC.

Connected through hyperedge HE-1 (induced by source paper "a nearly optimal lower bound on the approximate degree of ac 0"):
  with members:
    - "separations in query complexity based on pointer functions"
    - "dual polynomials for collision and element distinctness"
    - "distribution independent reliable learning"
    - "dual lower bounds for approximate degree and markov bernstein inequalities"
    - "faster private release of marginals on small databases"
    - "hardness amplification and the approximate degree of constant depth circuits"
    - "faster algorithms for privately releasing marginals"
    - "a separation of np and conp in multiparty communication complexity"

Connected through hyperedge HE-2 (induced by source paper "on the power of statistical zero knowledge"):
  with members:
    - "a nearly optimal lower bound on the approximate degree of ac 0"
    - "adaptivity vs postselection"
    - "dual polynomials for collision and element distinctness"
    - "hardness amplification and the approximate degree of constant depth circuits"
    - "verifying computations with streaming interactive proofs"
    - "on arthur merlin games in communication complexity"

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)