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: "on the hardness of approximate and exact bichromatic maximum inner product"
  Abstract: In this paper we study the (Bichromatic) Maximum Inner Product Problem (Max-IP), in which we are given sets $A$ and $B$ of vectors, and the goal is to find $a \in A$ and $b \in B$ maximizing inner product $a \cdot b$. Max-IP is very basic and serves as the base problem in the recent breakthrough of [Abboud et al., FOCS 2017] on hardness of approximation for polynomial-time problems. It is also used (implicitly) in the argument for hardness of exact $\ell_2$-Furthest Pair (and other important problems in computational geometry) in poly-log-log dimensions in [Williams, SODA 2018]. We have three main results regarding this problem. #R##N#First, we study the best multiplicative approximation ratio for Boolean Max-IP in sub-quadratic time. We show that, for Max-IP with two sets of $n$ vectors from $\{0,1\}^{d}$, there is an $n^{2 - \Omega(1)}$ time $\left( d/\log n \right)^{\Omega(1)}$-multiplicative-approximating algorithm, and we show this is conditionally optimal, as such a $\left(d/\log n\right)^{o(1)}$-approximating algorithm would refute SETH. #R##N#Second, we achieve a similar characterization for the best additive approximation error to Boolean Max-IP. We show that, for Max-IP with two sets of $n$ vectors from $\{0,1\}^{d}$, there is an $n^{2 - \Omega(1)}$ time $\Omega(d)$-additive-approximating algorithm, and this is conditionally optimal, as such an $o(d)$-approximating algorithm would refute SETH [Rubinstein, STOC 2018]. #R##N#Last, we revisit the hardness of solving Max-IP exactly for vectors with integer entries. We show that, under SETH, for Max-IP with sets of $n$ vectors from $\mathbb{Z}^{d}$ for some $d = 2^{O(\log^{*} n)}$, every exact algorithm requires $n^{2 - o(1)}$ time. With the reduction from [Williams, SODA 2018], it follows that $\ell_2$-Furthest Pair and Bichromatic $\ell_2$-Closest Pair in $2^{O(\log^{*} n)}$ dimensions require $n^{2 - o(1)}$ time.

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"
    - "a simple near linear pseudopolynomial time randomized algorithm for subset sum"

Connected through hyperedge HE-2 (induced by source paper "approximating apsp without scaling equivalence of approximate min plus and exact min max"):
  with members:
    - "on problems equivalent to min convolution"
    - "subquadratic approximation scheme for partition"
    - "hardness of approximate nearest neighbor search"
    - "from gap eth to fpt inapproximability clique dominating set and more"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "distributed pcp theorems for hardness of approximation in p"
    - "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor"
    - "a fast numerical method for max convolution and the application to efficient max product inference in bayesian networks"

Connected through hyperedge HE-3 (induced by source paper "conditional hardness of earth mover distance"):
  with members:
    - "preconditioning for the geometric transportation problem"
    - "faster algorithms for the geometric transportation problem"
    - "hardness of approximate nearest neighbor search"
    - "near linear time approximation algorithms for optimal transport via sinkhorn iteration"
    - "polynomial representations of threshold functions and algorithmic applications"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "edit distance cannot be computed in strongly subquadratic time unless seth is false"
    - "parallel algorithms for geometric graph problems"

Connected through hyperedge HE-4 (induced by source paper "interaction hard thresholding consistent sparse quadratic regression in sub quadratic time and space"):
  with members:
    - "high dimensional robust sparse regression"
    - "distributed pcp theorems for hardness of approximation in p"
    - "nonconvex sparse learning via stochastic optimization with progressive variance reduction"
    - "a greedy approach for budgeted maximum inner product search"
    - "diamond sampling for approximate maximum all pairs dot product mad search"
    - "on iterative hard thresholding methods for high dimensional m estimation"
    - "sparse polynomial learning and graph sketching"
    - "compressed matrix multiplication"

Connected through hyperedge HE-5 (induced by source paper "hardness of bichromatic closest pair with jaccard similarity"):
  with members:
    - "an equivalence class for orthogonal vectors"
    - "hardness of approximate nearest neighbor search"
    - "set similarity search beyond minhash"

Connected through hyperedge HE-6 (induced by source paper "fine grained complexity meets ip pspace"):
  with members:
    - "on problems equivalent to min convolution"
    - "hardness of approximate nearest neighbor search"
    - "tighter connections between formula sat and shaving logs"
    - "conditional lower bounds for all pairs max flow"
    - "conditional lower bounds for space time tradeoffs"
    - "conditional hardness for sensitivity problems"
    - "on the parameterized complexity of approximating dominating set"
    - "on the complexity of closest pair via polar pair of point sets"

Connected through hyperedge HE-7 (induced by source paper "dynamic set cover improved algorithms lower bounds"):
  with members:
    - "fully dynamic mis in uniformly sparse graphs"
    - "fully dynamic maximal independent set with sublinear update time"
    - "hardness of approximate nearest neighbor search"
    - "tight bounds on the round complexity of the distributed maximum coverage problem"
    - "distributed pcp theorems for hardness of approximation in p"
    - "dynamic algorithms for graph coloring"
    - "decremental single source reachability in planar digraphs"
    - "deterministic fully dynamic approximate vertex cover and fractional matching in o 1 amortized update time"

Connected through hyperedge HE-8 (induced by source paper "hardness of approximate nearest neighbor search"):
  with members:
    - "distributed pcp theorems for hardness of approximation in p"
    - "optimal las vegas locality sensitive data structures"
    - "randomized approximate nearest neighbor search with limited adaptivity"
    - "the curse of medium dimension for geometric problems in almost every norm"
    - "optimal hashing based time space trade offs for approximate near neighbors"
    - "polynomial representations of threshold functions and algorithmic applications"
    - "a faster subquadratic algorithm for finding outlier correlations"
    - "practical and optimal lsh for angular distance"

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.CC(Computational Complexity)