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: "sum of square proof for brascamp lieb type inequality"
  Abstract: Brascamp-Lieb inequality is an important mathematical tool in analysis, geometry and information theory. There are various ways to prove Brascamp-Lieb inequality such as heat flow method, Brownian motion and subadditivity of the entropy. While Brascamp-Lieb inequality is originally stated in Euclidean Space, discussed Brascamp-Lieb inequality for discrete Abelian group and discussed Brascamp-Lieb inequality for Markov semigroups. #R##N#Many mathematical inequalities can be formulated as algebraic inequalities which asserts some given polynomial is nonnegative. In 1927, Artin proved that any non- negative polynomial can be represented as a sum of squares of rational functions, which can be further formulated as a polynomial certificate of the nonnegativity of the polynomial. This is a Sum of Square proof of the inequality. Take the degree of the polynomial certificate as the degree of Sum of Square proof. The degree of an Sum of Square proof determines the complexity of generating such proof by Sum of Square algorithm which is a powerful tool for optimization and computer aided proof. #R##N#In this paper, we give a Sum of Square proof for some special settings of Brascamp- Lieb inequality following and and discuss some applications of Brascamp-Lieb inequality on Abelian group and Euclidean Sphere. If the original description of the inequality has constant degree and d is constant, the degree of the proof is also constant. Therefore, low degree sum of square algorithm can fully capture the power of low degree finite Brascamp-Lieb inequality.

Connected through hyperedge HE-1 (induced by source paper "algorithmic and optimization aspects of brascamp lieb inequalities via operator scaling"):
  with members:
    - "information theoretic perspectives on brascamp lieb inequality and its reverse"
    - "polynomial time tensor decompositions with sum of squares"
    - "smoothing brascamp lieb inequalities and strong converses for common randomness generation"
    - "operator scaling theory and applications"
    - "constructive noncommutative rank computation in deterministic polynomial time over fields of arbitrary characteristics"
    - "constructive noncommutative rank computation is in deterministic polynomial time"
    - "speeding up sum of squares for tensor decomposition and planted sparse vectors"
    - "a deterministic polynomial time algorithm for non commutative rational identity testing"

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)