human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "circuit depth reductions"):
  Abstract: The best known circuit lower bounds against unrestricted circuits remained around $3n$ for several decades. Moreover, the only known technique for proving lower bounds in this model, gate elimination, is inherently limited to proving lower bounds of less than $5n$. In this work, we suggest a first non-gate-elimination approach for obtaining circuit lower bounds. Namely, we prove that every (unbounded-depth) circuit of size $s$ can be expressed as an OR of $2^{s/3.9}$ $16$-CNFs. While this structural result does not immediately lead to new lower bounds, it suggests a new avenue of attack on them. #R##N#Our result complements the classical depth reduction result of Valiant which asserts that logarithmic-depth circuits of linear size can be computed by an OR of $2^{\varepsilon n}$ $n^{\delta}$-CNFs. It is known that no such graph-theoretic reduction can work for circuits of super-logarithmic depth. We overcome this limitation (for small circuits) by taking into account both the graph-theoretic and functional properties of circuits. #R##N#We show that qualitative improvements of the following pseudorandom constructions imply qualitative (from $3n$ to $\omega(n)$) improvement of size lower bounds for log-depth circuits via Valiant's reduction: dispersers for varieties, correlation with constant degree polynomials, matrix rigidity, and hardness for depth-$3$ circuits with constant bottom fan-in. On the other hand, now even modest quantitative improvements of the known constructions give elementary proofs of quantitatively stronger circuit lower bounds ($3.9n$ instead of $3n$).

Includes members:
  Member "limits on representing boolean functions by linear combinations of simple functions thresholds relus and low degree polynomials":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lower bounds against sparse symmetric functions of acc circuits expanding the reach of sat algorithms")
  Member "probabilistic polynomials and hamming nearest neighbors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "algorithms for similarity search and pseudorandomness")
  Member "two structural results for low degree polynomials and applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "csps with global modular constraints algorithms and hardness via polynomial representations")

Question: Please tell me which class the source paper 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)