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: "query matrices for retrieving binary vectors based on the hamming distance oracle"
  Abstract: The Hamming oracle returns the Hamming distance between an unknown binary n-vector x and a binary query n-vector y. The objective is to determine x uniquely using a sequence of m queries. What are the minimum number of queries required in the worst case? We consider the query ratio m=n to be our figure of merit and derive upper bounds on the query ratio by explicitly constructing (m;n) query matrices. We show that our recursive and algebraic construction results in query ratios arbitrarily close to zero. Our construction is based on codes of constant weight. A decoding algorithm for recovering the unknown binary vector is also described.

Connected through hyperedge HE-1 (induced by source paper "there are no bit parts for sign bits in black box attacks"):
  with members:
    - "certified adversarial robustness via randomized smoothing"
    - "explaining vulnerabilities of deep learning to adversarial malware binaries"
    - "a simple explanation for the existence of adversarial examples with small hamming distance"
    - "autozoom autoencoder based zeroth order optimization method for attacking black box neural networks"
    - "wild patterns ten years after the rise of adversarial machine learning"
    - "back to basics benchmarking canonical evolution strategies for playing atari"
    - "adversarial deep learning for robust detection of binary encoded malware"
    - "exploring the space of black box attacks on deep neural networks"

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.DM(Discrete Mathematics)