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: "limits on representing boolean functions by linear combinations of simple functions thresholds relus and low degree polynomials"
  Abstract: We consider the problem of representing Boolean functions exactly by "sparse" linear combinations (over $\mathbb{R}$) of functions from some "simple" class ${\cal C}$. In particular, given ${\cal C}$ we are interested in finding low-complexity functions lacking sparse representations. When ${\cal C}$ is the set of PARITY functions or the set of conjunctions, this sort of problem has a well-understood answer, the problem becomes interesting when ${\cal C}$ is "overcomplete" and the set of functions is not linearly independent. We focus on the cases where ${\cal C}$ is the set of linear threshold functions, the set of rectified linear units (ReLUs), and the set of low-degree polynomials over a finite field, all of which are well-studied in different contexts. #R##N#We provide generic tools for proving lower bounds on representations of this kind. Applying these, we give several new lower bounds for "semi-explicit" Boolean functions. For example, we show there are functions in nondeterministic quasi-polynomial time that require super-polynomial size: #R##N#$\bullet$ Depth-two neural networks with sign activation function, a special case of depth-two threshold circuit lower bounds. #R##N#$\bullet$ Depth-two neural networks with ReLU activation function. #R##N#$\bullet$ $\mathbb{R}$-linear combinations of $O(1)$-degree $\mathbb{F}_p$-polynomials, for every prime $p$ (related to problems regarding Higher-Order "Uncertainty Principles"). We also obtain a function in $E^{NP}$ requiring $2^{\Omega(n)}$ linear combinations. #R##N#$\bullet$ $\mathbb{R}$-linear combinations of $ACC \circ THR$ circuits of polynomial size (further generalizing the recent lower bounds of Murray and the author). #R##N#(The above is a shortened abstract. For the full abstract, see the paper.)

Connected through hyperedge HE-1 (induced by source paper "lower bounds against sparse symmetric functions of acc circuits expanding the reach of sat algorithms"):
  with members:
    - "polynomial representations of threshold functions and algorithmic applications"
    - "new algorithms and lower bounds for circuits with linear threshold gates"

Connected through hyperedge HE-2 (induced by source paper "toward super polynomial size lower bounds for depth two threshold circuits"):
  with members:
    - "on the hardness of approximate and exact bichromatic maximum inner product"
    - "tighter connections between formula sat and shaving logs"
    - "fine grained complexity meets ip pspace"
    - "weights at the bottom matter when the top is heavy"
    - "probabilistic rank and matrix rigidity"
    - "simulating branching programs with edit distance and friends or a polylog shaved is a lower bound made"
    - "super linear gate and super quadratic wire lower bounds for depth two and depth three threshold circuits"
    - "new algorithms and lower bounds for circuits with linear threshold gates"

Connected through hyperedge HE-3 (induced by source paper "circuit depth reductions"):
  with members:
    - "probabilistic polynomials and hamming nearest neighbors"
    - "two structural results for low degree polynomials and applications"

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)