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: "capacitated dynamic programming faster knapsack and graph algorithms"
  Abstract: One of the most fundamental problems in Theoretical Computer Science is the Knapsack problem. Given a set of n items with different weights and values, it asks to pick the most valuable subset whose total weight is below a capacity threshold T. Despite its wide applicability in various areas in computer science, operations research, and finance, the best known running time for the problem is O(T n). The main result of our work is an improvement of this algorithm for the special case where the number of distinct weights D is small, running in time O(T D). Previously, better algorithms for knapsack were known only for cases with weights and values bounded by M and V respectively, running in time O(nMV). In comparison, our algorithm implies a bound of O(nM^2) without any dependence on V. Additionally, for the unbounded knapsack problem, we provide an algorithm running in time O(M^2 log T). We also initiate a systematic study of general capacitated dynamic programming, of which knapsack is core problem. This problem asks to compute the maximum weight path of length k in an edge- or node-weighted directed acyclic graph. In a graph with m edges, these problems are solvable by dynamic programming in time O(km), and we explore under which conditions the dependence on k can be eliminated. We identify large classes of graphs where this is possible and apply our results to obtain linear time algorithms for the problem of k-sparse Delta-separated sequences. The main technical innovation behind our results is identifying and exploiting concavity that appears in relaxations and subproblems of the tasks we consider.

Connected through hyperedge HE-1 (induced by source paper "approximating subset sum is equivalent to min plus convolution"):
  with members:
    - "an improved fptas for 0 1 knapsack"
    - "approximating apsp without scaling equivalence of approximate min plus and exact min max"
    - "on problems equivalent to min convolution"
    - "subquadratic approximation scheme for partition"
    - "fast algorithms for knapsack via convolution and prediction"
    - "an equivalence class for orthogonal vectors"
    - "on integer programming and convolution"
    - "on the hardness of approximate and exact bichromatic maximum inner product"

Connected through hyperedge HE-2 (induced by source paper "on integer programming discrepancy and convolution"):
  with members:
    - "on problems equivalent to min convolution"
    - "on integer programming and convolution"
    - "tight complexity lower bounds for integer linear programming with few constraints"
    - "proximity results and faster algorithms for integer programming using the steinitz lemma"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "on the optimality of pseudo polynomial algorithms for integer programming"
    - "closing the gap for makespan scheduling via sparsification techniques"
    - "clustered integer 3sum via additive combinatorics"

Connected through hyperedge HE-3 (induced by source paper "fast modular subset sum using linear sketching"):
  with members:
    - "near optimal linear decision trees for k sum and related problems"
    - "seth based lower bounds for subset sum and bicriteria path"
    - "proximity results and faster algorithms for integer programming using the steinitz lemma"
    - "the decision tree complexity for k sum is at most nearly quadratic"
    - "a near linear pseudopolynomial time algorithm for subset sum"
    - "strong eth breaks with merlin and arthur short non interactive proofs of batch evaluation"
    - "losing weight by gaining edges"

Connected through hyperedge HE-4 (induced by source paper "fast algorithms for knapsack via convolution and prediction"):
  with members:
    - "on problems equivalent to min convolution"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "a near linear pseudopolynomial time algorithm for subset sum"
    - "clustered integer 3sum via additive combinatorics"
    - "a faster pseudopolynomial time algorithm for subset sum"

Connected through hyperedge HE-5 (induced by source paper "subset sum made simple"):
  with members:
    - "seth based lower bounds for subset sum and bicriteria path"
    - "a near linear pseudopolynomial time algorithm for subset sum"

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)