[Conference Paper][Journal Article]

Conference Paper

[AAAI] [AAMAS] [ACML] [AISTATS] [APWeb-WAIM] [COLT] [CVPR] [ECCV] [ICASSP] [ICDM] [ICLR] [ICML] [IJCAI] [INTERSPEECH] [KDD] [NeurIPS] [PAKDD] [PPSN] [PRICAI] [WSDM]

AAAI

• F.-M. Luo, S. Jiang, Y. Yu, Z. Zhang and Y.-F. Zhang. Adapt to Environment Sudden Changes by Learning a Context Sensitive Policy. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI'22), 2022.

• J.-Q. Yang, K.-B. Fan, H. Ma and D.-C. Zhan. RID-Noise: Towards Robust Inverse Design under Noisy Environments. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI'22), 2022.

• L. Yuan, J. Wang, F. Zhang, C. Wang, Z. Zhang, Y. Yu and C. Zhang. Multi-Agent Incentive Communication via Decentralized Teammate Modeling. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI'22), 2022.

• Y.-X. Sun and W. Wang. Exploiting mixed unlabeled data for detecting samples of seen and unseen out-of-distribution classes. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI'22), 2022.

• Y.-H. Cao and J. Wu. A Random CNN Sees Objects: One Inductive Bias of CNN and Its Applications. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI'22), 2022.

• Z.-M. Zhu, S. Jiang, Y.-R. Liu, Y. Yu and K. Zhang. Invariant action effect model for reinforcement learning. In: AAAI Conference on Artificial Intelligence (AAAI'22), 2022.

AAMAS

• Z.-X. Chen, X.-Q. Cai, Y. Jiang and Z.-H. Zhou. Anomaly Guided Policy Learning from Imperfect Demonstrations. In: Proceedings of the 21th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'22), 2022.

ACML

• M.-J. Yuan and W. Gao. Learning with Interactive Models over Decision-Dependent Distributions. In: Proceedings of the 14th Asian Conference on Machine Learning (ACML'22), 2022.

AISTATS

• G. Wang, M. Yang, L. Zhang and T. Yang. Momentum Accelerates the Convergence of Stochastic AUPRC Maximization. In: Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS'22), 2022.

• P. Zhao, Y.-X. Wang and Z.-H. Zhou. Non-stationary Online Learning with Memory and Non-stochastic Control. In: Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS'22), 2022.

• Y. Tao, Y. Wu, P. Zhao and D. Wang. Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits. In: Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS'22), 2022.

APWeb-WAIM

• S. Lu, Y. Miao, P. Yang, Y. Hu and L. Zhang. Non-Stationary Dueling Bandits for Online Learning to Rank. In: The Asia Pacific Web and Web-Age Information Management Joint International Conference on Web and Big Data (APWeb-WAIM'22), 2022.

COLT

• H. Luo, M. Zhang, P. Zhao and Z.-H. Zhou. Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits. In: Proceedings of the 35nd Annual Conference on Learning Theory (COLT'22), 2022.

• H. Luo, M. Zhang and P. Zhao. Adaptive Bandit Convex Optimization with Heterogeneous Curvature. In: Proceedings of the 35nd Annual Conference on Learning Theory (COLT'22), 2022.

CVPR

• L. Sui, C.-L. Zhang and J. Wu. Salvage of Supervision in Weakly Supervised Object Detection. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'22), 2022.

• X.-C. Li, Y.-C. Xu, S. Song, B. Li, Y. Li, Y. Shao and D.-C. Zhan. Federated Learning with Position-Aware Neurons. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'22), 2022.

ECCV

• M. Fu, Y.-H. Cao and J. Wu. Worst Case Matters for Few-Shot Recognition. In: European Conference on Computer Vision (ECCV'22), 2022.

• Y.-H. Cao, H. Yu and J. Wu. Training Vision Transformers with Only 2040 Images. In: European Conference on Computer Vision (ECCV'22), 2022.

• Y.-H. Cao, Y. Huang, P. Sun, J. Wu and S. Zhou. Synergistic Self-Supervised and Quantization Learning. In: European Conference on Computer Vision (ECCV'22), 2022.

ICASSP

• X.-C. Li, Y.-J. Wang, L. Gan and D.-C. Zhan. Exploring Transferability Measures and Domain Selection in Cross-Domain Slot Filling. In: IEEE International Conference on Acoustics, Speech and SP (ICASSP'22), 2022.

ICDM

• Y.-F. Ma and M. Li. Learning from the Multi-Level Abstraction of the Control Flow Graph via Alternating Propagation for Bug Localization. In: Proceedings of the 22th IEEE International Conference on Data Mining (ICDM'22), 2022.

ICLR

• H. Zhao, Y. Yu and K. X. Learning efficient online 3D bin packing on packing configuration trees. In: International Conference on Learning Representations (ICLR'22), 2022.

• S. Li, J. Zhang, J. Wang, Y. Yu and C. Zhang. Active hierarchical exploration with stable subgoal representation learning. In: International Conference on Learning Representations (ICLR'22), 2022.

• T. Wang, L. Zeng, W. Dong, Q. Yang, Y. Yu and C. Zhang. Context-aware sparse deep coordination graphs. In: International Conference on Learning Representations (ICLR'22), 2022.

• Y. Wang, K. Xue and C. Qian. Evolutionary Diversity Optimization with Clustering-based Selection for Reinforcement Learning. In: Proceedings of the 10th International Conference on Learning Representations (ICLR'22), 2022.

• Z. Li, T. Xu, Y. Yu and Z.-Q. Luo. Rethinking ValueDice: Does It Really Improve Performance?. In: Proceedings of the 10th International Conference on Learning Representations (ICLR'22 Blog Track), 2022.

ICML

• H. Qian, X.-H. Liu, C.-X. Su, A. Zhou and Y. Yu. The teaching dimension of regularized kernel learners. In: International Conference on Machine Learning (ICML'22), 2022.

• J.-Q. Guo, M.-Z. Teng, W. Gao and Z.-H. Zhou. Fast Provably Robust Decision Trees and Boosting. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), 2022.

• L. Zhang, G. Wang, J. Yi and T. Yang. A Simple yet Universal Strategy for Online Convex Optimization. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), 2022.

• L.-Z. Guo and Y.-F. Li. Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), 2022.

• M. Zhang, P. Zhao, H. Luo and Z.-H. Zhou. No-Regret Learning in Time-Varying Zero-Sum Games. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), 2022.

• P. Zhao, L.-F. Li and Z.-H. Zhou. Dynamic Regret of Online Markov Decision Processes. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), 2022.

• W. Jiang, B. Wang, Y. Wang, L. Zhang and T. Yang. Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), 2022.

• Z. Yuan, Y. Wu, Z.-H. Qiu, X. Du, L. Zhang, D. Zhou and T. Yang. Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), 2022.

• Z.-H. Qiu, Q. Hu, Y. Zhong, L. Zhang and T. Yang. Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), 2022.

IJCAI

• C. Bian, Y. Zhou and C. Qian. Robust Subset Selection by Greedy and Evolutionary Pareto Optimization. In: Proceedings of the 31th International Joint Conference on Artificial Intelligence (IJCAI'22), 2022.

• C. Qian. Towards Theoretically Grounded Evolutionary Learning. In: Proceedings of the 31th International Joint Conference on Artificial Intelligence (IJCAI'22), 2022.

• D. Xue, L. Yuan, Z. Zhang and Y. Yu. Efficient Multi-Agent Communication via Shapley Message Value. In: Proceedings of the 31th International Joint Conference on Artificial Intelligence (IJCAI'22), 2022.

• H. Shang, J.-L. Wu, W. Hong and C. Qian. Neural Network Pruning by Cooperative Coevolution. In: Proceedings of the 31th International Joint Conference on Artificial Intelligence (IJCAI'22), 2022.

• L. Yuan, C. Wang, J. Wang, F. Zhang, F. Chen, C. Guan, Z. Zhang, C. Zhang and Y. Yu. Multi-Agent Concentrative Coordination with Decentralized Task Representation. In: Proceedings of the 31th International Joint Conference on Artificial Intelligence (IJCAI'22), 2022.

• M.-Z. Qian, Z. Ai, T. Zhang and W. Gao. On the Optimization of Margin Distribution. In: Proceedings of the 31th International Joint Conference on Artificial Intelligence (IJCAI'22), 2022.

• Y. Zhu and K.-M. Ting. Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel (Extended Abstract). In: Proceedings of the 31th International Joint Conference on Artificial Intelligence (IJCAI'22), 2022.

INTERSPEECH

• X.-C. Li, J.-L. Tang, S. Song, B. Li, Y. Li, Y. Shao, L. Gan and D.-C. Zhan. Avoid Overfitting User Specific Information in Federated Keyword Spotting. In: Proceedings of the 23rd Conference of the International Speech Communication Association (INTERSPEECH'22), 2022.

• Y.-K. Zhang, D.-W. Zhou, H.-J. Ye and D.-C. Zhan. Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation. In: Proceedings of the 23rd Conference of the International Speech Communication Association (INTERSPEECH'22), 2022.

KDD

• J.-J. Shao, Y. Xu, Z. Cheng and Y.-F. Li. Active Model Adaptation Under Unknown Shift. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'22), 2022.

• X. Han, Y. Zhu, K.-M. Ting, D.-C. Zhan and G. Li. Streaming Hierarchical Clustering Based on Point-Set Kernel. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'22), 2022.

• Z.-Y. Zhang, Y.-Y. Qian, Y.-J. Zhang, Y. Jiang and Z.-H. Zhou. Adaptive Learning for Weakly Labeled Streams. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'22), 2022.

NeurIPS

• C. Wu, T. Li, Z. Zhang and Y. Yu. Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• C. Guan, F. Chen, L. Yuan, C. Wang, H. Yin, Z. Zhang and Y. Yu. Efficient Multi-agent Communication via Self-supervised Information Aggregation. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• J.-J. Shao, L.-Z. Guo, X.-W. Yang and Y.-F. Li. Active Model Adaptation Under Changed Distributions. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• J.-Q. Yang and D.-C. Zhan. Generalized Delayed Feedback Model with Post-Click Information in Recommender Systems. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• K. Xue, J. Xu, L. Yuan, M. Li, C. Qian, Z. Zhang and Y. Yu. Multi-agent Dynamic Algorithm Configuration. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• L. Chai and M. Li. Pyramid Attention for Source Code Summarization. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• L. Zhang, W. Jiang, J. Yi and T. Yang. Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• L.-Z. Guo, Y.-G. Zhang, Z.-F. Wu, J.-J. Shao and Y.-F. Li. SU-SSL: Maximize Performance in Unseen Classes and Maintain Safeness in Seen Classes. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• L. Song, K. Xue, X. Huang and C. Qian. Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• P. Zhao, Y.-F. Xie, L. Zhang and Z.-H. Zhou. Efficient Methods for Non-stationary Online Learning. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• R. Qin, F. Chen, T. Wang, L. Yuan, X. Wu, Y. Kang, Z. Zhang, C. Zhang and Y. Yu. Multi-agent policy transfer via task relationship modeling. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22 Workshop on Deep RL), 2022.

• R.-J. Qin, S. Gao, X. Zhang, Z. Xu, S. Huang, Z. Li, W. Zhang and Y. Yu. NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• S.-Q. Zhang and Z.-H. Zhou. Theoretically Provable Spiking Neural Networks. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• S.-H. Lyu, Y.-X. He and Z.-H. Zhou. Depth is More Powerful than Width with Prediction Concatenation in Deep Forest. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• S. Ding and W. Wang. Collaborative learning by detecting collaboration partners. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• T.-Z. Wang, T. Qin and Z.-H. Zhou. Sound and Complete Causal Identification with Latent Variables Given Local Background Knowledge. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• W. Jiang, G. Li, Y. Wang, L. Zhang and T. Yang. Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• X.-C. Li, W.-S. Fan, S. Song, Y. Li, B. Li, Y. Shao and D.-C. Zhan. Asymmetric Temperature Scaling Makes Larger Networks Teach Well Again. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• Y. Wan, W.-W. Tu and L. Zhang. Online Frank-Wolfe with Unknown Delays. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• Y.-X. Ding, X.-Z. Wu, K. Zhou and Z.-H. Zhou. Pre-Trained Model Reusability Evaluation for Small-Data Transfer Learning. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• Y. Bai, Y.-J. Zhang, P. Zhao, M. Sugiyama and Z.-H. Zhou. Adapting to Online Label Shift with Provable Guarantees. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

• Z.-H. Tan, Y. Xie, Y. Jiang and Z.-H. Zhou. Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), 2022.

PAKDD

• J. Li, J.-Q. Guo and W. Gao. Data Removal from an AUC Optimization Model. In: Proceedings of the26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'22), 2022.

• T. Wei, J.-X. Shi, Y.-F. Li and M.-L. Zhang. Prototypical Classifier for Robust Class-Imbalanced Learning. In: Proceedings of the26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'22), 2022.

• Y. Jian, J. Yi and L. Zhang. Adaptive Feature Generation for Online Continual Learning from Imbalanced Data. In: Proceedings of the26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'22), 2022.

PPSN

• C. Bian and C. Qian. Better Running Time of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) by Using Stochastic Tournament Selection. In: Proceedings of the 17th International Conference on Parallel Problem Solving from Nature (PPSN'22), 2022.

• J.-L. Wu, H. Shang, W. Hong and C. Qian. Robust Neural Network Pruning by Cooperative Coevolution. In: Proceedings of the 17th International Conference on Parallel Problem Solving from Nature (PPSN'22), 2022.

• Y.-C. Wu, Y.-X. He, C. Qian and Z.-H. Zhou. Multi-objective Evolutionary Ensemble Pruning Guided by Margin Distribution. In: Proceedings of the 17th International Conference on Parallel Problem Solving from Nature (PPSN'22), 2022.

• Z.-A. Zhang, C. Bian and C. Qian. Running Time Analysis of the (1+1)-EA using Surrogate Models on OneMax and LeadingOnes. In: Proceedings of the 17th International Conference on Parallel Problem Solving from Nature (PPSN'22), 2022.

PRICAI

• D.-M. Liu, H. Shang, W. Hong and C. Qian. Multi-Objective Evolutionary Instance Selection for Multi-Label Classification. In: Proceedings of the 19th Pacific Rim International Conference on Artificial Intelligence (PRICAI'22), 2022.

WSDM

• S. Lu, Y.-H. Zhou, J.-C. Shi, W. Zhu, Q. Yu, Q.-G. Chen, Q. Da and L. Zhang. Non-stationary Continuum-armed Bandits for Online Hyperparameter Optimization. In: Proceedings of the15th ACM International Conference on Web Search and Data Mining (WSDM'22), 2022.

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Journal Article and Book

[A] [F] [I] [J] [M] [N] [P] [S] [T] [计] [软]

Artificial Intelligence

• C. Qian, D.-X. Liu and Z.-H. Zhou. Result Diversification by Multi-objective Evolutionary Algorithms with Theoretical Guarantees. In: Artificial Intelligence, 2022, 309: 103737.

• W. Gao, F. Xu and Z.-H. Zhou. Towards convergence rate analysis of random forests for classification. In: Artificial Intelligence, 2022, 313:103788.

Frontiers of Computer Science

• Z.-H. Zhou. Rehearsal: Learning from Prediction to Decision. In: Frontiers of Computer Science, 2022, 16(4): 164352.

IEEE Transactions on Games

• R.-Z. Liu, H. Guo, X. Ji, Y. Yu, Z.-J. Pang, Z. Xiao, Y. Wu and T. Lu. Efficient reinforcement learning for StarCraft by abstract forward models and transfer learning. In: IEEE Transactions on Games, 2022, 14(2):94-307.

IEEE Transactions on Geoscience and Remote Sensing

• X. Song, S. Aryal, K.-M. Ting, Z. Liu and B. He. Spectral-Spatial Anomaly Detection of Hyperspectral Data Based on Improved Isolation Forest. In: IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 1-16 (2022).

IEEE Transactions on Knowledge and Data Engineering

• M. Pang, K.-M. Ting, P. Zhao and Z.-H. Zhou. Improving Deep Forest by Screening. In: IEEE Transactions on Knowledge and Data Engineering, 2022, 34(9): 4298-4312.

• Z.-Y. Zhang, P. Zhao, Y. Jiang and Z.-H. Zhou. Learning From Incomplete and Inaccurate Supervision. In: IEEE Transactions on Knowledge and Data Engineering, 2022, 34(12):5854-5868.

IEEE Transactions on Neural Networks and Learning Systems

• G. Li, P. Yang, C. Qian, R. Hong and K. Tang. Stage-wise Magnitude-based Pruning for Recurrent Neural Networks. In: IEEE Transactions on Neural Networks and Learning Systems, 2022, in press.

• J. Wang and Z.-H. Zhou. Margin Distribution Analysis. In: IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(8): 3948-3960.

IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

• J.-H. Wu, S.-Q. Zhang, Y. Jiang and Z.-H. Zhou. Theoretical Exploration of Flexible Transmitter Model. In: IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022, in press.

IEEE Transactions on Neural Networks and Learning Systems

• B.-J. Hou, L. Zhang and Z.-H. Zhou. Prediction With Unpredictable Feature Evolution. In: IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(10): 5706-5715.

IEEE Transactions on Pattern Analysis and Machine Intelligence

• H.-J. Ye, L. Han and D.-C. Zhan. Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, in press.

• T. Xu, Z. Li and Y. Yu. Error bounds of imitating policies and environments for reinforcement learning. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 44(10):6968-6980.

• Y.-Q. Hu, X.-H. Liu, S.-Q. Li and Y. Yu. Cascaded algorithm selection with extreme-region UCB bandit. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 44(10):6782-6794.

• Y. Wan and L. Zhang. Efficient Adaptive Online Learning via Frequent Directions. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 44(10): 6910-6923.

Information Systems

• Y. Zhu, K.-M. Ting, Y. Jin and M. Angelova. Hierarchical clustering that takes advantage of both density-peak and density-connectivity. In: Information Systems, 2022, 103:101871(2022).

Journal of Machine Learning Research

• R.-Z. Liu, Z.-J. Pang, Z.-Y. Meng, W. Wang, Y. Yu and T. Lu. On efficient reinforcement learning for full-length game of StarCraft II. In: Journal of Artificial Intelligence Research, 2022, in press.

• Y. Wan, G. Wang, W.-W. Tu and L. Zhang. Projection-free Distributed Online Learning with Sublinear Communication Complexity. In: Journal of Machine Learning Research, 2022, 23(172): 1-53.

Machine Learning

• P. Tan, Z.-H. Tan, Y. Jiang and Z.-H. Zhou. Towards Enabling Learnware to Handle Heterogeneous Feature Spaces. In: Machine Learning, 2022, in press.

• Y. Wan, W.-W. Tu and L. Zhang. Online Strongly Convex Optimization with Unknown Delays. In: Machine Learning, 2022, 111(3): 871-893.

• Y.-F. Ma and M. Li. The Flowing Nature Matters: Feature Learning from the Control Flow Graph of Source Code for Bug Localization. In: Machine Learning, 2022, 111(3): 853-870.

• Y.-F. Zhang, F.-M. Luo and Y. Yu. Improve generated adversarial imitation learning with reward variance regularization. In: Machine Learning, 2022, 111:977-995.

National Science Review

• Z.-H. Zhou. Open-environment machine learning. In: National Science Review, 2022, 9(8): nwac123.

Neural Networks

• S.-Q. Zhang, W. Gao and Z.-H. Zhou. Towards Understanding Theoretical Advantages of Complex-Reaction Networks. In: Neural Networks, 2022, 151:80-93.

• S.-H. Lyu, L. Wang and Z.-H. Zhou. Improving Generalization of Neural Networks by Leveraging Margin Distribution. In: Neural Networks, 2022, 151:48-60.

Proceedings of the VLDB Endowment

• K.-M. Ting, Z. Liu, H. Zhang and Y. Zhu. A New Distributional Treatment for Time Series and An Anomaly Detection Investigation. In: Proceedings of the VLDB Endowment, 2022, 15(11): 2321-2333.

Science China: Information Sciences

• H. Sun and M. Li. Enhancing Unsupervised Domain Adaptation by Exploiting the Conceptual Consistency of Multiple Self-Supervised Tasks. In: Science China: Information Sciences, 2022, in press.

• J. Cao, L. Yuan, J. Wang, S. Zhang, C. Zhang, Y. Yu and D.-C. Zhan. LINDA: Multi-Agent Local Information Decomposition for Awareness of Teammates. In: Science China: Information Sciences, 2022, in press.

• T. Wei, H. Wang, W.-W. Tu and Y.-F. Li. Robust model selection for positive and unlabeled learning with constraints. In: Science China: Information Sciences, 2022, 65(11): 212101.

• Y. Wan, W.-W. Tu and L. Zhang. Strongly Adaptive Online Learning over Partial Intervals. In: Science China: Information Sciences, 2022, 65(10): 202101.

• Y.-R. Liu, Y.-Q. Hu, H. Qian, Y. Yu and C. Qian. ZOOpt: Toolbox for Derivative-Free Optimization. In: Science China: Information Sciences, 2022, 65: 20710.

Transactions on Machine Learning Research

• L. Han, H.-J. Ye and D.-C. Zhan. On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning. In: Transactions on Machine Learning Research, 2022, in press.

计算机科学与探索

• 常田, 章宗长, 俞扬. 随机集成策略迁移. In: 计算机科学与探索, 2022, 16(11): 2531-2536.

• 李新春, 詹德川. 使用多分类器的分布式模型重用技术. In: 计算机科学与探索, 2022, 16(10):2310-2319.

软件学报

• 吕沈欢, 陈一赫, 姜远. 基于交互表示的多标记深度森林方法. In: 软件学报, 2022, in press.

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