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: "isomorphism problems for tensors groups and cubic forms completeness and reductions"
  Abstract: In this paper we consider the problems of testing isomorphism of tensors, $p$-groups, cubic forms, algebras, and more, which arise from a variety of areas, including machine learning, group theory, and cryptography. These problems can all be cast as orbit problems on multi-way arrays under different group actions. Our first two main results are: #R##N#1. All the aforementioned isomorphism problems are equivalent under polynomial-time reductions, in conjunction with the recent results of Futorny-Grochow-Sergeichuk (Lin. Alg. Appl., 2019). #R##N#2. Isomorphism of $d$-tensors reduces to isomorphism of 3-tensors, for any $d \geq 3$. #R##N#Our results suggest that these isomorphism problems form a rich and robust equivalence class, which we call Tensor Isomorphism-complete, or TI-complete. We then leverage the techniques used in the above results to prove two first-of-their-kind results for Group Isomorphism (GpI): #R##N#3. We give a reduction from GpI for $p$-groups of exponent $p$ and small class ($c < p$) to GpI for $p$-groups of exponent $p$ and class 2. The latter are widely believed to be the hardest cases of GpI, but as far as we know, this is the first reduction from any more general class of groups to this class. #R##N#4. We give a search-to-decision reduction for isomorphism of $p$-groups of exponent $p$ and class 2 in time $|G|^{O(\log \log |G|)}$. While search-to-decision reductions for Graph Isomorphism (GI) have been known for more than 40 years, as far as we know this is the first non-trivial search-to-decision reduction in the context of GpI. #R##N#Our main technique for (1), (3), and (4) is a linear-algebraic analogue of the classical graph coloring gadget, which was used to obtain the search-to-decision reduction for GI. This gadget construction may be of independent interest and utility. The technique for (2) gives a method for encoding an arbitrary tensor into an algebra.

Connected through hyperedge HE-1 (induced by source paper "general linear group action on tensors a candidate for post quantum cryptography"):
  with members:
    - "operator scaling via geodesically convex optimization invariant theory and polynomial identity testing"
    - "efficient algorithms for tensor scaling quantum marginals and moment polytopes"
    - "alternating minimization scaling algorithms and the null cone problem from invariant theory"
    - "algorithms based on algebras and their applications to isomorphism of polynomials with one secret group isomorphism and polynomial identity testing"
    - "constructive noncommutative rank computation is in deterministic polynomial time"
    - "solving the isomorphism of polynomials with two secrets problem for all pairs of quadratic forms"
    - "polynomial time algorithms for quadratic isomorphism of polynomials the regular case"
    - "on the lattice isomorphism problem"

Connected through hyperedge HE-2 (induced by source paper "derandomization and absolute reconstruction for sums of powers of linear forms"):
  with members:
    - "orbits of monomials and factorization into products of linear forms"
    - "algorithms based on algebras and their applications to isomorphism of polynomials with one secret group isomorphism and polynomial identity testing"
    - "reconstruction algorithms for sums of affine powers"
    - "a deterministic polynomial time algorithm for non commutative rational identity testing"
    - "non commutative edmonds problem and matrix semi invariants"
    - "quasipolynomial time identity testing of non commutative and read once oblivious algebraic branching programs"
    - "symmetric tensor decomposition"

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)