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 "relational linear programs"):
  Abstract: We propose relational linear programming, a simple framework for combing linear programs (LPs) and logic programs. A relational linear program (RLP) is a declarative LP template defining the objective and the constraints through the logical concepts of objects, relations, and quantified variables. This allows one to express the LP objective and constraints relationally for a varying number of individuals and relations among them without enumerating them. Together with a logical knowledge base, effectively a logical program consisting of logical facts and rules, it induces a ground LP. This ground LP is solved using lifted linear programming. That is, symmetries within the ground LP are employed to reduce its dimensionality, if possible, and the reduced program is solved using any off-the-shelf LP solver. In contrast to mainstream LP template languages like AMPL, which features a mixture of declarative and imperative programming styles, RLP's relational nature allows a more intuitive representation of optimization problems over relational domains. We illustrate this empirically by experiments on approximate inference in Markov logic networks using LP relaxations, on solving Markov decision processes, and on collective inference using LP support vector machines.

Includes members:
  Member "tight lower and upper bounds for the complexity of canonical colour refinement":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hypergraph isomorphism for groups with restricted composition factors")
  Member "dimension reduction via colour refinement":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards a practical k dimensional weisfeiler leman algorithm")
  Member "rockit exploiting parallelism and symmetry for map inference in statistical relational models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "beyond markov logic efficient mining of prediction rules in large graphs")
  Member "automorphism groups of graphical models and lifted variational inference":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "generating and sampling orbits for lifted probabilistic inference")
  Member "first order mixed integer linear programming":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the symbolic interior point method")
  Member "counting belief propagation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "lifted hybrid variational inference")
  Member "tuffy scaling up statistical inference in markov logic networks using an rdbms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "nonlinear equation solving a faster alternative to feedforward computation")

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.AI(Artificial Intelligence)