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 "a faster cutting plane method and its implications for combinatorial and convex optimization"):
  Abstract: We improve upon the running time for finding a point in a convex set given a separation oracle. In particular, given a separation oracle for a convex set $K\subset \mathbb{R}^n$ contained in a box of radius $R$, we show how to either find a point in $K$ or prove that $K$ does not contain a ball of radius $\epsilon$ using an expected $O(n\log(nR/\epsilon))$ oracle evaluations and additional time $O(n^3\log^{O(1)}(nR/\epsilon))$. This matches the oracle complexity and improves upon the $O(n^{\omega+1}\log(nR/\epsilon))$ additional time of the previous fastest algorithm achieved over 25 years ago by Vaidya for the current matrix multiplication constant $\omega<2.373$ when $R/\epsilon=n^{O(1)}$. #R##N#Using a mix of standard reductions and new techniques, our algorithm yields improved runtimes for solving classic problems in continuous and combinatorial optimization: #R##N#Submodular Minimization: Our weakly and strongly polynomial time algorithms have runtimes of $O(n^2\log nM\cdot\text{EO}+n^3\log^{O(1)}nM)$ and $O(n^3\log^2 n\cdot\text{EO}+n^4\log^{O(1)}n)$, improving upon the previous best of $O((n^4\text{EO}+n^5)\log M)$ and $O(n^5\text{EO}+n^6)$. #R##N#Matroid Intersection: Our runtimes are $O(nrT_{\text{rank}}\log n\log (nM) +n^3\log^{O(1)}(nM))$ and $O(n^2\log (nM) T_{\text{ind}}+n^3 \log^{O(1)} (nM))$, achieving the first quadratic bound on the query complexity for the independence and rank oracles. In the unweighted case, this is the first improvement since 1986 for independence oracle. #R##N#Submodular Flow: Our runtime is $O(n^2\log nCU\cdot\text{EO}+n^3\log^{O(1)}nCU)$, improving upon the previous bests from 15 years ago roughly by a factor of $O(n^4)$. #R##N#Semidefinite Programming: Our runtime is $\tilde{O}(n(n^2+m^{\omega}+S))$, improving upon the previous best of $\tilde{O}(n(n^{\omega}+m^{\omega}+S))$ for the regime where the number of nonzeros $S$ is small.

Includes members:
  Member "using optimization to obtain a width independent parallel simpler and faster positive sdp solver":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "positive semidefinite programming mixed parallel and width independent")
  Member "efficient inverse maintenance and faster algorithms for linear programming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "solving tall dense linear programs in nearly linear time")
  Member "powers of tensors and fast matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "bayesian truthful mechanisms for job scheduling from bi criterion approximation algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "persuasion and incentives through the lens of duality")
  Member "uniform sampling for matrix approximation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sketching transformed matrices with applications to natural language processing")
  Member "reducing revenue to welfare maximization approximation algorithms and other generalizations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal mechanisms for selling two items to a single buyer having uniformly distributed valuations")
  Member "path finding ii an o m sqrt n algorithm for the minimum cost flow problem":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "speeding up linear programming using randomized linear algebra")
  Member "optimal multi dimensional mechanism design reducing revenue to welfare maximization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a permutation equivariant neural network architecture for auction design")

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)