附录A：2019顶会统计数据

{
    "AAAI 2019": {
        "paper": "How to Combine Tree-Search Methods in Reinforcement Learning",
        "Theoretical": "False",
        "Awards": "Outstanding Paper"
    },
    "AAAI 2019": {
        "paper": "Solving Imperfect-Information Games via Discounted Regret Minimization",
        "Theoretical": "True",
        "Awards": "Outstanding Paper Honorable Mention"
    },
    "AAAI 2019": {
        "paper": "Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference",
        "Theoretical": "False",
        "Awards": "Outstanding Student Paper"
    },
    "AAAI 2019": {
        "paper": "Learning to Teach in Cooperative Multiagent Reinforcement Learning",
        "Theoretical": "False",
        "Awards": "Outstanding Student Paper Honorable Mention"
    },
     "ICLR 2019": {
        "paper": "Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks",
        "Theoretical": "False",
        "Awards": "Best Paper"
    },
     "ICLR 2019": {
        "paper": "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks",
        "Theoretical": "True",
        "Awards": "Best Paper"
    },
    "ICML 2019": {
        "paper": "Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations",
        "Theoretical": "True",
        "Awards": "Best Paper"
    },
    "ICML 2019": {
        "paper": "Rates of Convergence for Sparse Variational Gaussian Process Regression",
        "Theoretical": "True",
        "Awards": "Best Paper"
    },
    "CVPR 2019": {
        "paper": "A Theory of Fermat Paths for Non-Line-of-Sight Shape Reconstruction",
        "Theoretical": "True",
        "Awards": "Best Paper"
    },
    "CVPR 2019": {
        "paper": "Reinforced Cross-Modal Matching & Self-Supervised Imitation Learning for Vision-Language Navigation",
        "Theoretical": "False",
        "Awards": "Best Student Paper"
    },
    "ACL 2019": {
        "paper": "Bridging the Gap between Training and Inference for Neural Machine Translation",
        "Theoretical": "False",
        "Awards": "Best Long Paper"
    },
    "ACL 2019": {
        "paper": "Do you know that Florence is packed with visitors? Evaluating state-of-the-art models of speaker commitment",
        "Theoretical": "False",
        "Awards": "Best Short Paper"
    },
    "IJCAI 2019": {
        "paper": "Boosting for Comparison-Based Learning",
        "Theoretical": "True",
        "Awards": "Distinguished Paper"
    },
    "IJCAI 2019": {
        "paper": "Clause Elimination for SAT and QSAT",
        "Theoretical": "False",
        "Awards": "IJCAI-JAIR Best Paper"
    },
    "ICCV 2019": {
        "paper": "SinGAN：Learning a Generative Model From a Single Natural Image",
        "Theoretical": "False",
        "Awards": "Best Paper (Marr Prize)"
    },
    "ICCV 2019": {
        "paper": "PLMP-Point-Line Minimal Problems in Complete Multi-View Visibility",
        "Theoretical": "True",
        "Awards": "Best Student Paper"
    },
    "NeurIPS 2019": {
        "paper": "Distribution-Independent PAC Learning of Halfspaces with Massart Noise",
        "Theoretical": "True",
        "Awards": "Outstanding Paper"
    },
    "NeurIPS 2019": {
        "paper": "Uniform convergence may be unable to explain generalization in deep learning",
        "Theoretical": "True",
        "Awards": "Outstanding New Directions Paper Award"
    },
    "NeurIPS 2019": {
        "paper": "Nonparametric density estimation & convergence of GANs under Besov IPM losses",
        "Theoretical": "True",
        "Awards": "Honorable Mention Outstanding Paper"
    },
    "NeurIPS 2019": {
        "paper": "Fast and Accurate Least-Mean-Squares Solvers",
        "Theoretical": "False",
        "Awards": "Honorable Mention Outstanding Paper"
    },
    "NeurIPS 2019": {
        "paper": "Putting An End to End-to-End: Gradient-Isolated Learning of Representations",
        "Theoretical": "False",
        "Awards": "Honorable Mention Outstanding New Directions Paper"
    },
    "NeurIPS 2019": {
        "paper": "Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations",
        "Theoretical": "False",
        "Awards": "Honorable Mention Outstanding New Directions Paper"
    },  
}