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: "equality saturation a new approach to optimization"
  Abstract: Optimizations in a traditional compiler are applied sequentially, with each#N#optimization destructively modifying the program to produce a transformed#N#program that is then passed to the next optimization. We present a new approach#N#for structuring the optimization phase of a compiler. In our approach,#N#optimizations take the form of equality analyses that add equality information#N#to a common intermediate representation. The optimizer works by repeatedly#N#applying these analyses to infer equivalences between program fragments, thus#N#saturating the intermediate representation with equalities. Once saturated, the#N#intermediate representation encodes multiple optimized versions of the input#N#program. At this point, a profitability heuristic picks the final optimized#N#program from the various programs represented in the saturated representation.#N#Our proposed way of structuring optimizers has a variety of benefits over#N#previous approaches: our approach obviates the need to worry about optimization#N#ordering, enables the use of a global optimization heuristic that selects among#N#fully optimized programs, and can be used to perform translation validation,#N#even on compilers other than our own. We present our approach, formalize it,#N#and describe our choice of intermediate representation. We also present#N#experimental results showing that our approach is practical in terms of time#N#and space overhead, is effective at discovering intricate optimization#N#opportunities, and is effective at performing translation validation for a#N#realistic optimizer.

Connected through hyperedge HE-1 (induced by source paper "spores sum product optimization via relational equality saturation for large scale linear algebra"):
  with members:
    - "using e graphs for cad parameter inference"
    - "on optimizing operator fusion plans for large scale machine learning in systemml"
    - "laradb a minimalist kernel for linear and relational algebra computation"
    - "in database learning with sparse tensors"
    - "solving the join ordering problem via mixed integer linear programming"
    - "faq questions asked frequently"

Connected through hyperedge HE-2 (induced by source paper "spoc search based pseudocode to code"):
  with members:
    - "neural program repair by jointly learning to localize and repair"
    - "frangel component based synthesis with control structures"
    - "seq2sql generating structured queries from natural language using reinforcement learning"
    - "nl2bash a corpus and semantic parser for natural language interface to the linux operating system"
    - "naps natural program synthesis dataset"
    - "mapping language to code in programmatic context"
    - "coarse to fine decoding for neural semantic parsing"
    - "retrieval based neural code generation"

Connected through hyperedge HE-3 (induced by source paper "linnea automatic generation of efficient linear algebra programs"):
  with members:
    - "the linear algebra mapping problem"
    - "automatic generation of efficient linear algebra programs"
    - "the generalized matrix chain algorithm"
    - "non linear associative commutative many to one pattern matching with sequence variables"
    - "efficient pattern matching in python"
    - "matchpy a pattern matching library"
    - "sparsity based correction of exponential artifacts"
    - "a parallel implementation of the ensemble kalman filter based on modified cholesky decomposition"

Connected through hyperedge HE-4 (induced by source paper "automatic generation of efficient linear algebra programs"):
  with members:
    - "the generalized matrix chain algorithm"
    - "non linear associative commutative many to one pattern matching with sequence variables"
    - "efficient pattern matching in python"
    - "image restoration by iterative denoising and backward projections"
    - "matchpy a pattern matching library"
    - "sparsity based correction of exponential artifacts"
    - "a parallel implementation of the ensemble kalman filter based on modified cholesky decomposition"
    - "on a natural dynamics for linear programming"

Connected through hyperedge HE-5 (induced by source paper "using e graphs for cad parameter inference"):
  with members:
    - "automatically leveraging mapreduce frameworks for data intensive applications"
    - "csgnet neural shape parser for constructive solid geometry"
    - "learning to infer graphics programs from hand drawn images"
    - "programmatic and direct manipulation together at last"
    - "program synthesis from polymorphic refinement types"

Connected through hyperedge HE-6 (induced by source paper "on the representation of partially specified implementations and its application to the optimization of linear algebra kernels on gpu"):
  with members:
    - "tvm end to end optimization stack for deep learning"
    - "tensor comprehensions framework agnostic high performance machine learning abstractions"

Connected through hyperedge HE-7 (induced by source paper "cobra a framework for cost based rewriting of database applications"):
  with members:
    - "runtime optimization of join location in parallel data management systems"
    - "program transformations for asynchronous and batched query submission"
    - "efficient and extensible algorithms for multi query optimization"

Connected through hyperedge HE-8 (induced by source paper "combinatorial register allocation and instruction scheduling"):
  with members:
    - "survey on combinatorial register allocation and instruction scheduling"
    - "horn clauses as an intermediate representation for program analysis and transformation"

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.PL(Programming Languages)