Linglong Kong
Orcid: 0000-0003-3011-9216
According to our database1,
Linglong Kong
authored at least 64 papers
between 2010 and 2024.
Collaborative distances:
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Bibliography
2024
Comput. Stat., June, 2024
Predicting Bitcoin Market Trends with Enhanced Technical Indicator Integration and Classification Models.
CoRR, 2024
Debiasing with Sufficient Projection: A General Theoretical Framework for Vector Representations.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024
Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Appl. Intell., December, 2023
J. Multivar. Anal., 2023
J. Comput. Graph. Stat., 2023
Comput. Stat. Data Anal., 2023
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023
Exploring the Training Robustness of Distributional Reinforcement Learning Against Noisy State Observations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Explaining Anatomical Shape Variability: Supervised Disentangling with A Variational Graph Autoencoder.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Proceedings of the International Conference on Machine Learning, 2023
Opposite Online Learning via Sequentially Integrated Stochastic Gradient Descent Estimators.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
ACM Trans. Web, 2022
Frontiers Big Data, 2022
Associations between Longitudinal Gestational Weight Gain and Scalar Infant Birth Weight: A Bayesian Joint Modeling Approach.
Entropy, 2022
Flexible quantile contour estimation for multivariate functional data: Beyond convexity.
Comput. Stat. Data Anal., 2022
How Does Value Distribution in Distributional Reinforcement Learning Help Optimization?
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
MTGnet: Multi-Task Spatiotemporal Graph Convolutional Networks for Air Quality Prediction.
Proceedings of the International Joint Conference on Neural Networks, 2022
Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
J. Multivar. Anal., 2021
Comput. Stat., 2021
Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm.
CoRR, 2021
L$^{2}$NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning.
CoRR, 2021
CoRR, 2021
Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations.
CoRR, 2021
Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
L2NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021
2020
ACM Trans. Knowl. Discov. Data, 2020
Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions.
Entropy, 2020
2019
Sparse wavelet estimation in quantile regression with multiple functional predictors.
Comput. Stat. Data Anal., 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019
2018
IEEE Trans. Medical Imaging, 2018
2017
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017
2016
Neurocomputing, 2016
Regularized quantile regression under heterogeneous sparsity with application to quantitative genetic traits.
Comput. Stat. Data Anal., 2016
House Price Modeling over Heterogeneous Regions with Hierarchical Spatial Functional Analysis.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016
2015
Proceedings of the Information Processing in Medical Imaging, 2015
2011
2010
J. Multivar. Anal., 2010
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010