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 "t visne interactive assessment and interpretation of t sne projections"):
  Abstract: t-Distributed Stochastic Neighbor Embedding (t-SNE) for the visualization of multidimensional data has proven to be a popular approach, with successful applications in a wide range of domains. Despite their usefulness, t-SNE projections can be hard to interpret or even misleading, which hurts the trustworthiness of the results. Understanding the details of t-SNE itself and the reasons behind specific patterns in its output may be a daunting task, especially for non-experts in dimensionality reduction. In this work, we present t-viSNE, an interactive tool for the visual exploration of t-SNE projections that enables analysts to inspect different aspects of their accuracy and meaning, such as the effects of hyper-parameters, distance and neighborhood preservation, densities and costs of specific neighborhoods, and the correlations between dimensions and visual patterns. We propose a coherent, accessible, and well-integrated collection of different views for the visualization of t-SNE projections. The applicability and usability of t-viSNE are demonstrated through hypothetical usage scenarios with real data sets. Finally, we present the results of a user study where the tool's effectiveness was evaluated. By bringing to light information that would normally be lost after running t-SNE, we hope to support analysts in using t-SNE and making its results better understandable.

Includes members:
  Member "supporting analysis of dimensionality reduction results with contrastive learning":
    also connected through other hyperedges:
      (none)
  Member "fast interpolation based t sne for improved visualization of single cell rna seq data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tree sne hierarchical clustering and visualization using t sne")
  Member "clustrophile 2 guided visual clustering analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ablate variate and contemplate visual analytics for discovering neural architectures")
  Member "rulematrix visualizing and understanding classifiers with rules":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "explainer a visual analytics framework for interactive and explainable machine learning")
  Member "a visual interaction framework for dimensionality reduction based data exploration":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "semantic concept spaces guided topic model refinement using word embedding projections")
  Member "dimreader axis lines that explain non linear projections":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "genetic programming for evolving a front of interpretable models for data visualisation")
  Member "t sne cuda gpu accelerated t sne and its applications to modern data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "gpgpu linear complexity t sne optimization")
  Member "clustering with t sne provably":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "tree sne hierarchical clustering and visualization using t sne")

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)