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: "communication vs distributed computation an alternative trade off curve"
  Abstract: In this paper, we revisit the communication vs. distributed computing trade-off, studied within the framework of MapReduce in [1]. An implicit assumption in the aforementioned work is that each server performs all possible computations on all the files stored in its memory. Our starting observation is that, if servers can compute only the intermediate values they need, then storage constraints do not directly imply computation constraints. We examine how this affects the communication-computation trade-off and suggest that the trade-off be studied with a predetermined storage constraint. We then proceed to examine the case where servers need to perform computationally intensive tasks, and may not have sufficient time to perform all computations required by the scheme in [1]. Given a threshold that limits the computational load, we derive a lower bound on the associated communication load, and propose a heuristic scheme that achieves in some cases the lower bound.

Connected through hyperedge HE-1 (induced by source paper "low complexity distributed computing via binary matrices with extension to stragglers"):
  with members:
    - "coded caching based on combinatorial designs"
    - "speeding up distributed machine learning using codes"
    - "storage computation and communication a fundamental tradeoff in distributed computing"
    - "a fundamental tradeoff between computation and communication in distributed computing"
    - "a unified coding framework for distributed computing with straggling servers"

Connected through hyperedge HE-2 (induced by source paper "a fundamental storage communication tradeoff in distributed computing with straggling nodes"):
  with members:
    - "speeding up distributed machine learning using codes"
    - "storage computation and communication a fundamental tradeoff in distributed computing"
    - "speeding up distributed gradient descent by utilizing non persistent stragglers"
    - "hierarchical coding for distributed computing"
    - "placement delivery array design through strong edge coloring of bipartite graphs"
    - "a storage computation communication tradeoff for distributed computing"
    - "coded distributed computing with node cooperation substantially increases speedup factors"
    - "straggler mitigation in distributed matrix multiplication fundamental limits and optimal coding"

Connected through hyperedge HE-3 (induced by source paper "resolvable designs for speeding up distributed computing"):
  with members:
    - "leveraging coding techniques for speeding up distributed computing"
    - "coded computing for distributed graph analytics"
    - "compressed coded distributed computing"
    - "a new combinatorial design of coded distributed computing"
    - "coded caching schemes with reduced subpacketization from linear block codes"
    - "the benefit of being flexible in distributed computation"
    - "a fundamental tradeoff between computation and communication in distributed computing"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-4 (induced by source paper "an exact quantized decentralized gradient descent algorithm"):
  with members:
    - "speeding up distributed machine learning using codes"
    - "coded computing for distributed graph analytics"
    - "quantized decentralized consensus optimization"
    - "a fundamental tradeoff between computation and communication in distributed computing"
    - "qsgd communication efficient sgd via gradient quantization and encoding"
    - "fast distributed gradient methods"
    - "distributed autonomous online learning regrets and intrinsic privacy preserving properties"

Connected through hyperedge HE-5 (induced by source paper "wireless mapreduce distributed computing"):
  with members:
    - "leveraging coding techniques for speeding up distributed computing"
    - "speeding up distributed machine learning using codes"
    - "federated learning strategies for improving communication efficiency"
    - "distributed computing with heterogeneous communication constraints the worst case computation load and proof by contradiction"
    - "coded computing for distributed graph analytics"
    - "hierarchical coding for distributed computing"
    - "compressed coded distributed computing"
    - "coded distributed computing with node cooperation substantially increases speedup factors"

Connected through hyperedge HE-6 (induced by source paper "near optimal coded data shuffling for distributed learning"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "speeding up distributed machine learning using codes"
    - "on the fundamental limits of coded data shuffling for distributed learning systems"
    - "a pliable index coding approach to data shuffling"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "low subpacketization schemes for coded caching"
    - "latency analysis of coded computation schemes over wireless networks"
    - "coded convolution for parallel and distributed computing within a deadline"

Connected through hyperedge HE-7 (induced by source paper "coded computing for distributed graph analytics"):
  with members:
    - "coded cooperative computation for internet of things"
    - "leveraging coding techniques for speeding up distributed computing"
    - "speeding up distributed machine learning using codes"
    - "distributed computing with heterogeneous communication constraints the worst case computation load and proof by contradiction"
    - "compressed coded distributed computing"
    - "fundamental limits of coded linear transform"
    - "fundamental resource trade offs for encoded distributed optimization"
    - "rateless codes for near perfect load balancing in distributed matrix vector multiplication"

Connected through hyperedge HE-8 (induced by source paper "fundamental limits of decentralized data shuffling"):
  with members:
    - "coded distributed computing with heterogeneous function assignments"
    - "cascaded coded distributed computing on heterogeneous networks"
    - "embedded index coding"
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "leveraging coding techniques for speeding up distributed computing"
    - "speeding up distributed machine learning using codes"
    - "storage computation and communication a fundamental tradeoff in distributed computing"
    - "coded computing for distributed graph analytics"

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.IT(Information Theory)