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: "toward super polynomial size lower bounds for depth two threshold circuits"
  Abstract: Proving super-polynomial size lower bounds for $\textsf{TC}^0$, the class of constant-depth, polynomial-size circuits of Majority gates, is a notorious open problem in complexity theory. A major frontier is to prove that $\textsf{NEXP}$ does not have poly-size $\textsf{THR} \circ \textsf{THR}$ circuit (depth-two circuits with linear threshold gates). #R##N#In recent years, R.~Williams proposed a program to prove circuit lower bounds via improved algorithms. In this paper, following Williams' framework, we show that the above frontier question can be resolved by devising slightly faster algorithms for several fundamental problems: #R##N#1. Shaving Logs for $\textsf{$\ell_2$-Furthest-Pair}$. An $n^2 \textrm{poly}(d) / \log^{\omega(1)} n$ time algorithm for $\textsf{$\ell_2$-Furthest-Pair}$ in $\mathbb{R}^d$ for polylogarithmic $d$ implies $\textsf{NEXP}$ has no polynomial size $\textsf{THR} \circ \textsf{THR}$ circuits. The same holds for Hopcroft's problem, $\textsf{Bichrom.-$\ell_2$-Closest-Pair}$ and Integer $\textsf{Max-IP}$. #R##N#2. Shaving Logs for Approximate $\textsf{Bichrom.-$\ell_2$-Closest-Pair}$. An $n^2 \textrm(d) / \log^{\omega(1)} n$ time algorithm for $(1+1/\log^{\omega(1)} n)$-approximation to $\textsf{Bichrom.-$\ell_2$-Closest-Pair}$ or $\textsf{Bichrom.-$\ell_1$-Closest-Pair}$ for polylogarithmic $d$ implies $\textsf{NEXP}$ has no polynomial size $\textsf{SYM}\circ\textsf{THR}$ circuits. #R##N#3. Shaving Logs for Modest Dimension Boolean $\textsf{Max-IP}$. An $n^2 / \log^{\omega(1)} n$ time algorithm for Bichromatic Maximum Inner Product with vector dimension $d = n^\epsilon$ for any small constant $\epsilon$ would imply $\textsf{NEXP}$ has no polynomial size $\textsf{THR} \circ \textsf{THR}$ circuits. Note there is an $n^2\textrm{polylog}(n)$ time algorithm via fast rectangle matrix multiplication. #R##N#Our results build on two structure lemmas for threshold circuits.

Connected through hyperedge HE-1 (induced by source paper "on closest pair in euclidean metric monochromatic is as hard as bichromatic"):
  with members:
    - "an equivalence class for orthogonal vectors"
    - "on the hardness of approximate and exact bichromatic maximum inner product"
    - "distributed pcp theorems for hardness of approximation in p"
    - "on the complexity of closest pair via polar pair of point sets"
    - "polynomial representations of threshold functions and algorithmic applications"
    - "powers of tensors and fast matrix multiplication"

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)