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 "eth hardness of approximating 2 csps and directed steiner network"):
  Abstract: We study the 2-ary constraint satisfaction problems (2-CSPs), which can be stated as follows: given a constraint graph $G=(V,E)$, an alphabet set $\Sigma$ and, for each $\{u, v\}\in E$, a constraint $C_{uv} \subseteq \Sigma\times\Sigma$, the goal is to find an assignment $\sigma: V \to \Sigma$ that satisfies as many constraints as possible, where a constraint $C_{uv}$ is satisfied if $(\sigma(u),\sigma(v))\in C_{uv}$. #R##N#While the approximability of 2-CSPs is quite well understood when $|\Sigma|$ is constant, many problems are still open when $|\Sigma|$ becomes super constant. One such problem is whether it is hard to approximate 2-CSPs to within a polynomial factor of $|\Sigma| |V|$. Bellare et al. (1993) suggested that the answer to this question might be positive. Alas, despite efforts to resolve this conjecture, it remains open to this day. #R##N#In this work, we separate $|V|$ and $|\Sigma|$ and ask a related but weaker question: is it hard to approximate 2-CSPs to within a polynomial factor of $|V|$ (while $|\Sigma|$ may be super-polynomial in $|V|$)? Assuming the exponential time hypothesis (ETH), we answer this question positively by showing that no polynomial time algorithm can approximate 2-CSPs to within a factor of $|V|^{1 - o(1)}$. Note that our ratio is almost linear, which is almost optimal as a trivial algorithm gives a $|V|$-approximation for 2-CSPs. #R##N#Thanks to a known reduction, our result implies an ETH-hardness of approximating Directed Steiner Network with ratio $k^{1/4 - o(1)}$ where $k$ is the number of demand pairs. The ratio is roughly the square root of the best known ratio achieved by polynomial time algorithms (Chekuri et al., 2011; Feldman et al., 2012). #R##N#Additionally, under Gap-ETH, our reduction for 2-CSPs not only rules out polynomial time algorithms, but also FPT algorithms parameterized by $|V|$. Similar statement applies for DSN parameterized by $k$.

Includes members:
  Member "hardness of approximate nearest neighbor search":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the i o complexity of the k nearest neighbor problem")
  Member "on the hardness of approximate and exact bichromatic maximum inner product":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximating subset sum is equivalent to min plus convolution")
  Member "improved approximation algorithms for projection games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "improved approximation algorithm for the dense 3 subhypergraph problem")
  Member "distributed pcp theorems for hardness of approximation in p":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "graphs cannot be indexed in polynomial time for sub quadratic time string matching unless seth fails")
  Member "detecting communities is hard and counting them is even harder":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "inapproximability of vc dimension and littlestone s dimension")
  Member "settling the complexity of computing approximate two player nash equilibria":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "complexity theory game theory and economics the barbados lectures")
  Member "approximating spanners and directed steiner forest upper and lower bounds":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "graph spanners a tutorial review")
  Member "approximation of non boolean 2csp":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a note on degree vs gap of min rep label cover and improved inapproximability for connectivity problems")

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)