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: "machine learner for automated reasoning 0 4 and 0 5"
  Abstract: Machine Learner for Automated Reasoning (MaLARea) is a learning and reasoning system for proving in large formal libraries where thousands of theorems are available when attacking a new conjecture, and a large number of related problems and proofs can be used to learn specific theorem-proving knowledge. The last version of the system has by a large margin won the 2013 CASC LTB competition. This paper describes the motivation behind the methods used in MaLARea, discusses the general approach and the issues arising in evaluation of such system, and describes the Mizar@Turing100 and CASC'24 versions of MaLARea.

Connected through hyperedge HE-1 (induced by source paper "holist an environment for machine learning of higher order theorem proving"):
  with members:
    - "gamepad a learning environment for theorem proving"
    - "reinforcement learning of theorem proving"
    - "deep network guided proof search"
    - "holstep a machine learning dataset for higher order logic theorem proving"
    - "tactictoe learning to reason with hol4 tactics"
    - "premise selection for theorem proving by deep graph embedding"
    - "squad 100 000 questions for machine comprehension of text"
    - "wavenet a generative model for raw audio"

Connected through hyperedge HE-2 (induced by source paper "ml fv heartsuit a survey on the application of machine learning to formal verification"):
  with members:
    - "learning a sat solver from single bit supervision"
    - "explaining how a deep neural network trained with end to end learning steers a car"
    - "mastering chess and shogi by self play with a general reinforcement learning algorithm"
    - "deep network guided proof search"
    - "deepmath deep sequence models for premise selection"
    - "end to end learning for self driving cars"
    - "android malware detection an eigenspace analysis approach"
    - "a bayesian approach to tackling hard computational problems"

Connected through hyperedge HE-3 (induced by source paper "reinforcement learning of theorem proving"):
  with members:
    - "atpboost learning premise selection in binary setting with atp feedback"
    - "mastering chess and shogi by self play with a general reinforcement learning algorithm"
    - "deep network guided proof search"
    - "tactictoe learning to reason with hol4 tactics"
    - "deepmath deep sequence models for premise selection"
    - "xgboost a scalable tree boosting system"
    - "holophrasm a neural automated theorem prover for higher order logic"
    - "premise selection and external provers for hol4"

Connected through hyperedge HE-4 (induced by source paper "enigma efficient learning based inference guiding machine"):
  with members:
    - "monte carlo connection prover"
    - "mizar 40 for mizar 40"
    - "sepia search for proofs using inferred automata"
    - "blistr the blind strategymaker"
    - "males a framework for automatic tuning of automated theorem provers"
    - "learning assisted automated reasoning with flyspeck"

Connected through hyperedge HE-5 (induced by source paper "mizar 40 for mizar 40"):
  with members:
    - "premise selection for mathematics by corpus analysis and kernel methods"
    - "blistr the blind strategymaker"
    - "hol y hammer online atp service for hol light"
    - "theorem proving in large formal mathematics as an emerging ai field"
    - "learning assisted automated reasoning with flyspeck"
    - "atp and presentation service for mizar formalizations"

Connected through hyperedge HE-6 (induced by source paper "initial experiments with tptp style automated theorem provers on acl2 problems"):
  with members:
    - "encoding monomorphic and polymorphic types"
    - "mizar 40 for mizar 40"
    - "premise selection for mathematics by corpus analysis and kernel methods"
    - "blistr the blind strategymaker"
    - "hol y hammer online atp service for hol light"
    - "theorem proving in large formal mathematics as an emerging ai field"
    - "learning assisted automated reasoning with flyspeck"
    - "atp and presentation service for mizar formalizations"

Connected through hyperedge HE-7 (induced by source paper "learning assisted theorem proving with millions of lemmas"):
  with members:
    - "mizar 40 for mizar 40"
    - "premise selection for mathematics by corpus analysis and kernel methods"
    - "lemma mining over hol light"
    - "blistr the blind strategymaker"
    - "hol y hammer online atp service for hol light"
    - "theorem proving in large formal mathematics as an emerging ai field"
    - "learning assisted automated reasoning with flyspeck"
    - "atp and presentation service for mizar formalizations"

Connected through hyperedge HE-8 (induced by source paper "blistr the blind strategymaker"):
  with members:
    - "premise selection for mathematics by corpus analysis and kernel methods"
    - "learning assisted automated reasoning with flyspeck"

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.LG(Machine Learning)