human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "Human Face Detection in Visual Scenes"
  Abstract: We present a neural network-based face detection system. A retinally connected neural network examines small windows of an image, and decides whether each window contains a face. The system arbitrates between multiple networks to improve performance over a single network. We use a bootstrap algorithm for training, which adds false detections into the training set as training progresses. This eliminates the difficult task of manually selecting non-face training examples, which must be chosen to span the entire space of non-face images. Comparisons with another state-of-the-art face detection system are presented; our system has better performance in terms of detection and false-positive rates.

Connected through hyperedge HE-1 (induced by source paper "Support Vector Machines: Training and Applications"):
  with members:
    - "Massive Data Discrimination via Linear Support Vector Machines"
    - "Nonlinear Prediction of Chaotic Time Series Using Support Vector Machines"
    - "Extracting Support Data for a Given Task"

Connected through hyperedge HE-2 (induced by source paper "Face Recognition: A Hybrid Neural Network Approach"):
  with members:
    - "From Data Distributions to Regularization in Invariant Learning"
    - "Evaluation of Pattern Classifiers for Fingerprint and OCR Applications"

Connected through hyperedge HE-3 (induced by source paper "A Neural Network Based Head Tracking System"):
  with members:
    (none)

Question: Please tell me which class the center node belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Neural_Networks