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 "joint alignment from pairwise differences with a noisy oracle"):
  Abstract: In this work we consider the problem of recovering n discrete random variables \(x_i\in \{0,\ldots ,k-1\}, 1 \le i \le n\) with the smallest possible number of queries to a noisy oracle that returns for a given query pair \((x_i,x_j)\) a noisy measurement of their modulo k pairwise difference, i.e., \(y_{ij} = x_i-x_j \ (\mathrm {mod}\ k)\). This is a joint discrete alignment problem with important applications in computer vision [12, 23], graph mining [20], and spectroscopy imaging [22]. Our main result is a recovery algorithm (up to some offset) that solves with high probability the non-convex maximum likelihood estimation problem using \(O(n^{1+o(1)})\) queries.

Includes members:
  Member "optimal learning of joint alignments with a faulty oracle":
    also connected through other hyperedges:
      (none)
  Member "predicting positive and negative links with noisy queries theory practice":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "correlation clustering with adaptive similarity queries")
  Member "the projected power method an efficient algorithm for joint alignment from pairwise differences":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal learning of joint alignments with a faulty oracle")
  Member "clustering via crowdsourcing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed clustering in the anonymized space with local differential privacy")
  Member "a semidefinite program for unbalanced multisection in the stochastic block model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards learning sparsely used dictionaries with arbitrary supports")
  Member "beyond triangles a distributed framework for estimating 3 profiles of large graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a fast counting method for 6 motifs with low connectivity")
  Member "mathematical and algorithmic analysis of network and biological data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient algorithms for densest subgraph discovery")
  Member "exact recovery in the stochastic block model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "renyi entropy bounds on the active learning cost performance tradeoff")

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.DS(Data Structures and Algorithms)