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 "the weighted tsetlin machine compressed representations with weighted clauses"):
  Abstract: The Tsetlin Machine (TM) is an interpretable mechanism for pattern recognition that constructs conjunctive clauses from data. The clauses capture frequent patterns with high discriminating power, providing increasing expression power with each additional clause. However, the resulting accuracy gain comes at the cost of linear growth in computation time and memory usage. In this paper, we present the Weighted Tsetlin Machine (WTM), which reduces computation time and memory usage by \emph{weighting} the clauses. Real-valued weighting allows one clause to replace multiple and supports fine-tuning the impact of each clause. Our novel scheme simultaneously learns both the composition of the clauses and their weights. Furthermore, we increase training efficiency by replacing $k$ Bernoulli trials of success probability $p$ with a uniform sample of average size $p k$, the size drawn from a binomial distribution. In our empirical evaluation, the WTM achieved the same accuracy as the TM on MNIST, IMDb, and Connect-4, requiring only $1/4$, $1/3$, and $1/50$ of the clauses, respectively. With the same number of clauses, the WTM outperformed the TM, obtaining peak test accuracies of respectively $98.58\%$, $90.15\%$, and $87.49\%$. Finally, our novel sampling scheme reduced sample generation time by a factor of $7$.

Includes members:
  Member "the convolutional tsetlin machine":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "concept whitening for interpretable image recognition")
  Member "a scheme for continuous input to the tsetlin machine with applications to forecasting disease outbreaks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the convolutional tsetlin machine")
  Member "the regression tsetlin machine a tsetlin machine for continuous output problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a regression tsetlin machine with integer weighted clauses for compact pattern representation")
  Member "using the tsetlin machine to learn human interpretable rules for high accuracy text categorization with medical applications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a regression tsetlin machine with integer weighted clauses for compact pattern representation")
  Member "the tsetlin machine a game theoretic bandit driven approach to optimal pattern recognition with propositional logic":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a regression tsetlin machine with integer weighted clauses for compact pattern representation")

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.LG(Machine Learning)