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: "hamilton jacobi reachability a brief overview and recent advances"
  Abstract: Hamilton-Jacobi (HJ) reachability analysis is an important formal verification method for guaranteeing performance and safety properties of dynamical systems; it has been applied to many small-scale systems in the past decade. Its advantages include compatibility with general nonlinear system dynamics, formal treatment of bounded disturbances, and the availability of well-developed numerical tools. The main challenge is addressing its exponential computational complexity with respect to the number of state variables. In this tutorial, we present an overview of basic HJ reachability theory and provide instructions for using the most recent numerical tools, including an efficient GPU-parallelized implementation of a Level Set Toolbox for computing reachable sets. In addition, we review some of the current work in high-dimensional HJ reachability to show how the dimensionality challenge can be alleviated via various general theoretical and application-specific insights.

Connected through hyperedge HE-1 (induced by source paper "an inductive synthesis framework for verifiable reinforcement learning"):
  with members:
    - "concolic testing for deep neural networks"
    - "programmatically interpretable reinforcement learning"
    - "reachability analysis of deep neural networks with provable guarantees"
    - "verifiable reinforcement learning via policy extraction"
    - "feature guided black box safety testing of deep neural networks"
    - "deep reinforcement learning an overview"
    - "towards generalization and simplicity in continuous control"
    - "reluplex an efficient smt solver for verifying deep neural networks"

Connected through hyperedge HE-2 (induced by source paper "generating robust supervision for learning based visual navigation using hamilton jacobi reachability"):
  with members:
    - "an efficient reachability based framework for provably safe autonomous navigation in unknown environments"
    - "generalization through simulation integrating simulated and real data into deep reinforcement learning for vision based autonomous flight"
    - "neural autonomous navigation with riemannian motion policy"
    - "combining optimal control and learning for visual navigation in novel environments"
    - "deep drone racing learning agile flight in dynamic environments"
    - "chauffeurnet learning to drive by imitating the best and synthesizing the worst"
    - "driving policy transfer via modularity and abstraction"
    - "beauty and the beast optimal methods meet learning for drone racing"

Connected through hyperedge HE-3 (induced by source paper "an efficient reachability based framework for provably safe autonomous navigation in unknown environments"):
  with members:
    - "combining optimal control and learning for visual navigation in novel environments"
    - "safe and complete real time planning and exploration in unknown environments"
    - "a lyapunov based approach to safe reinforcement learning"
    - "safe motion planning in unknown environments optimality benchmarks and tractable policies"
    - "a general safety framework for learning based control in uncertain robotic systems"
    - "fastrack a modular framework for fast and guaranteed safe motion planning"
    - "constrained policy optimization"
    - "provably safe and robust drone routing via sequential path planning a case study in san francisco and the bay area"

Connected through hyperedge HE-4 (induced by source paper "recommendations and user agency the reachability of collaboratively filtered information"):
  with members:
    - "sequential learning over implicit feedback for robust large scale recommender systems"
    - "when collaborative filtering meets reinforcement learning"
    - "on the difficulty of evaluating baselines a study on recommender systems"
    - "are we really making much progress a worrying analysis of recent neural recommendation approaches"
    - "efficient search for diverse coherent explanations"
    - "the social cost of strategic classification"
    - "causal embeddings for recommendation"
    - "exploring author gender in book rating and recommendation"

Connected through hyperedge HE-5 (induced by source paper "a hamilton jacobi reachability based framework for predicting and analyzing human motion for safe planning"):
  with members:
    - "human motion trajectory prediction a survey"
    - "combining optimal control and learning for visual navigation in novel environments"
    - "safe motion planning in unknown environments optimality benchmarks and tractable policies"
    - "a general safety framework for learning based control in uncertain robotic systems"
    - "multimodal probabilistic model based planning for human robot interaction"
    - "guided cost learning deep inverse optimal control via policy optimization"
    - "forecasting interactive dynamics of pedestrians with fictitious play"
    - "finding approximate pomdp solutions through belief compression"

Connected through hyperedge HE-6 (induced by source paper "a learnable safety measure"):
  with members:
    - "learning agile and dynamic motor skills for legged robots"
    - "feedback control for cassie with deep reinforcement learning"
    - "real time control for autonomous racing based on viability theory"
    - "a general safety framework for learning based control in uncertain robotic systems"
    - "bayesian optimization using domain knowledge on the atrias biped"
    - "safe exploration in finite markov decision processes with gaussian processes"
    - "safe controller optimization for quadrotors with gaussian processes"
    - "safe exploration in markov decision processes"

Connected through hyperedge HE-7 (induced by source paper "numerical verification of affine systems with up to a billion dimensions"):
  with members:
    - "reach set approximation through decomposition with low dimensional sets and high dimensional matrices"
    - "reachability analysis of large linear systems with uncertain inputs in the krylov subspace"
    - "an efficient algorithm for vertex enumeration of two dimensional projection of polytopes"
    - "order reduction abstractions for safety verification of high dimensional linear systems"
    - "bounded verification with on the fly discrepancy computation"

Connected through hyperedge HE-8 (induced by source paper "reachability based safety guarantees using efficient initializations"):
  with members:
    - "bridging the gap between safety and real time performance in receding horizon trajectory design for mobile robots"
    - "fastrack a modular framework for fast and guaranteed safe motion planning"
    - "robust sequential path planning under disturbances and adversarial intruder"
    - "synthesis of separable controlled invariant sets for modular local control design"

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.SY(Systems and Control)