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: "optimal las vegas reduction from one way set reconciliation to error correction"
  Abstract: Suppose we have two players $A$ and $C$, where player $A$ has a string $s[0..u-1]$ and player $C$ has a string $t[0..u-1]$ and none of the two players knows the other's string. Assume that $s$ and $t$ are both over an integer alphabet $[\sigma]$, where the first string contains $n$ non-zero entries. We would wish to answer to the following basic question. Assuming that $s$ and $t$ differ in at most $k$ positions, how many bits does player $A$ need to send to player $C$ so that he can recover $s$ with certainty? Further, how much time does player $A$ need to spend to compute the sent bits and how much time does player $C$ need to recover the string $s$? #R##N#This problem has a certain number of applications, for example in databases, where each of the two parties possesses a set of $n$ key-value pairs, where keys are from the universe $[u]$ and values are from $[\sigma]$ and usually $n\ll u$. In this paper, we show a time and message-size optimal Las Vegas reduction from this problem to the problem of systematic error correction of $k$ errors for strings of length $\Theta(n)$ over an alphabet of size $2^{\Theta(\log\sigma+\log (u/n))}$. The additional running time incurred by the reduction is linear randomized for player $A$ and linear deterministic for player $B$, but the correction works with certainty. When using the popular Reed-Solomon codes, the reduction gives a protocol that transmits $O(k(\log u+\log\sigma))$ bits and runs in time $O(n\cdot\mathrm{polylog}(n)(\log u+\log\sigma))$ for all values of $k$. The time is randomized for player $A$ (encoding time) and deterministic for player $C$ (decoding time). The space is optimal whenever $k\leq (u\sigma)^{1-\Omega(1)}$.

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.DS(Data Structures and Algorithms)