Natural Interaction for Tri-Co Robots

Multimodal Emotion Analysis

[2024]

[2024-1]  Yuan Z, Zhang B, Xu H, et al. OpenVNA: A Framework for Analyzing the Behavior of Multimodal LanguageUnderstanding System under Noisy Scenarios[C]//Proceedings of the 62th Annual Meeting of the Association for Computational Linguistics: System Demonstrations


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[2024-1]  Yuan Z, Zhang B, Xu H, et al. Meta Noise Adaption Framework for Multimodal Sentiment Analysis With Feature Noise[J]. IEEE Transactions on Multimedia, 2024.


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[2024-7]  Zhang B, Yuan Z, Xu H, et al. Crossmodal Translation Based Meta Weight Adaption for Robust Image-Text Sentiment Analysis[J]. IEEE Transactions on Multimedia, 2024.


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[2023]

[2023-1]  Mao H, Zhang B, Xu H, et al. Robust-MSA: Understanding the Impact of Modality Noise on Multimodal Sentiment Analysis[C]. Proceedings of the AAAI Conference on Artificial Intelligence. 2023: 16458-16460.


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[2023-2] Yuan Z, Liu Y, Xu X, et al. Noise Imitation based Adversarial Training for Robust Multimodal Sentiment Analysis[J].IEEE Transactions on Multimedia(2023).


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[2022]

[2022-1] Xu H, Yuan Z, Zhao K, et al. GAR-Net: A Graph Attention Reasoning Network for Conversation Understanding[J]. Knowledge-Based Systems. 2022, 240(3):108055.


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[2022-2] Yu W, Hua Xu. Co-Attentive Multi-Task Convolutional Neural Network for Facial Expression Recognition[J]. Pattern Recognition. 2022, 123: 108401.


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[2022-3] Mao H, Yuan Z, Xu H, et al. M-SENA: An Integrated Platform for Multimodal Sentiment Analysis[C]. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. 2022: 204-213.


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[2022-4] Mao H, Zhang B, Xu H, et al. An End-to-End Traditional Chinese Medicine Constitution Assessment System Based on Multimodal Clinical Feature Representation and Fusion[C]. Proceedings of the 36th AAAI Conference on Artificial Intelligence: System Demonstrations. 2022: 13200 - 13202.


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[2022-5] Liu Y, Yuan Z, Mao H, et al. Make Acoustic and Visual Cues Matter: CH-SIMS v2. 0 Dataset and AV-Mixup Consistent Module[C]. Proceedings of the 24th International Conference on Multimodal Interaction. 2022: 247 - 258.


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[2021]

[2021-1]  Yuan Z, Li W, Xu H, et al. Transformer-based Feature Reconstruction Network for Robust Multimodal Sentiment Analysis[C]. Proceedings of the 29th ACM International Conference on Multimedia. 2021: 4400-4407.


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[2021-2] Yu W, Xu H, Yuan Z, et al. Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment Analysis[C]. Proceedings of the 35th AAAI Conference on Artificial Intelligence. 2021, 35(12): 10790-10797.


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[2020]

[2020-1] Li H, Xu H. Deep Reinforcement Learning for Robust Emotional Classification in Facial Expression Recognition[J]. Knowledge-Based Systems. 2020, 204: 106172.


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[2020-2] Yang K, Xu H, Gao K. CM-BERT: Cross-Modal BERT for Text-Audio Sentiment Analysis[C]. Proceedings of the 28th ACM International Conference on Multimedia. 2020: 12-16.


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[2020-3] Yu W, Xu H, Meng F, et al. CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotations of Modality[C]. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020: 3718–3727.


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[2020-4] Xu Y, Xu H, Zou J. HGFM: A Hierarchical Grained and Feature Model for Acoustic Emotion Recognition[C]. Proceedings of the 2020 IEEE International Conference on Acoustics, Speech and Signal Processing. 2020: 6499-6503.


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[2020-5]  Cao Y, Xu H. SATNet: Symmetric Adversarial Transfer Network Based on Two-Level Alignment Strategy Towards Cross-Domain Sentiment Classification[C]. Proceedings of the 34th AAAI Conference on Artificial Intelligence: Student Tracks. 2020, 34(10): 13763-13764.


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[2020-6] Wang X, Xu H, Sun X, et al. Combining Fine-Tuning with a Feature-Based Approach for Aspect Extraction on Reviews[C]. Proceedings of the 34th AAAI Conference on Artificial Intelligence: Student Tracks. 2020, 34(10): 13951-13952.


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Multimodal Intent Understanding

[2024]

[2024-1] Zhang H, Xin W, Xu H, et al. MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations. Proceedings of the 12th International Conference on Learning Representations


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[2023]

[2023-12] Q Zhou, H Xu, H Li, H Zhang, et al. Token-Level Contrastive Learning with Modality-Aware Prompting for Multimodal Intent Recognition[C]. Proceedings of the AAAI Conference on Artificial Intelligence.


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[2023-11] Zhang H, Xu H, Xin W, et al. A Clustering Framework for Unsupervised and Semi-supervised New Intent Discovery[J]. IEEE Transactions on Knowledge and Data Engineering.


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[2023-1] Zhang H, Xu H, Zhao S, et al. Learning Discriminative Representations and Decision Boundaries for Open Intent Detection[J]. IEEE Transactions on Audio, Speech, and Language Processing.


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[2022]

[2022-1] Zhang H, Xu H, Wang X, et al. MIntRec: A New Dataset for Multimodal Intent Recognition[C]. Proceedings of the 30th ACM International Conference on Multimedia. 2022: 1688–1697.


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[2021]

[2021-1] Zhang H, Xu H, Lin T, et al. Discovering New Intents with Deep Aligned Clustering[C]. Proceedings of the 35th AAAI Conference on Artificial Intelligence. 2021, 35(16), 14365-14373.


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[2021-2] Zhang H, Xu H, Lin T. Deep Open Intent Classification with Adaptive Decision Boundary[C]. Proceedings of the 35th AAAI Conference on Artificial Intelligence. 2021, 35(16): 14374-14382.


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[2021-3] Zhang H, Li X, Xu H, et al. TEXTOIR: An Integrated and Visualized Platform for Text Open Intent Recognition[C]. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations. 2021: 167–174.


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[2020]

[2020-1] Lin T, Xu H, Zhang H. Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement[C]. Proceedings of the 34th AAAI Conference on Artificial Intelligence: System Demonstrations. 2020: 8360-8367.


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[2020-1] Lin T, Xu H, Zhang H. Constrained Self-supervised Clustering for Discovering New Intents[C]. Proceedings of the 34th AAAI Conference on Artificial Intelligence: Student Tracks. 2020, 34(10): 13863-13864.


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[2019]

[2019-1] Lin T, Xu H. A Post-processing Method for Detecting Unknown Intent of Dialogue System via Pre-trained Deep Neural Network Classifier[J]. Knowledge-Based Systems. 2019, 186: 104979.


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[2019-2] Lin T, Xu H. Deep Unknown Intent Detection with Margin Loss[C]. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019: 5491–5496.


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Reading Comprehension Related to Question Answering

[2022]

[2022-1] Wu Z, Xu H. Trustworthy Machine Reading Comprehension with Conditional Adversarial Calibration[J]. Applied Intelligence. 2022: 1-18.


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[2022-2] Wu Z, Fang J, Xu H, et al. An In-depth Interactive and Visualized Platform for Evaluating and Analyzing MRC Models[C]. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 2022: 5044-5048.


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[2022-3] Wu Z, Xu H, Fang J, et al. Continual Machine Reading Comprehension via Uncertainty-aware Fixed Memory and Adversarial Domain Adaptation[C]. Proceedings of the 6th Findings of the Association for Computational Linguistics. 2022: 2330–2339.


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[2020]

[2020-1] Wu Z, Xu H. Improving the Robustness of Machine Reading Comprehension Model with Hierarchical Knowledge and Auxiliary Unanswerability Prediction[J]. Knowledge-Based Systems. 2020, 203: 106075.


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[2020-2] Wu Z, Xu H. A Multi-Task Learning Machine Reading Comprehension Model for Noisy Document[C]. Proceedings of the 34th AAAI Conference on Artificial Intelligence: Student Abstract. 2020, 34(10): 13963-13964.


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Entity Recognition and Relation Extraction for Interactive Information

[2022]

[2022-1] Zhao K, Xu H, Yang J, et al. Consistent Representation Learning for Continual Relation Extraction[C]. Proceedings of Findings of the 6th Association for Computational Linguistics. 2022: 3402–3411.


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[2021]

[2021-1] Zhao K, Xu H, Cheng Y, et al. Representation Iterative Fusion Based on Heterogeneous Graph Neural Network for Joint Entity and Relation Extraction[J]. Knowledge-Based Systems. 2021, 219: 106888.


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[2020]

[2020-1] Xie Y, Xu H, Li J, et al. Heterogeneous Graph Neural Networks for Noisy Few-Shot Relation Classification[J]. Knowledge-Based Systems. 2020, 194: 105548.


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[2020-2] Xie Y, Xu H, Yang C, et al. Multi-Channel Convolutional Neural Networks with Adversarial Training for Few-Shot Relation Classification[C]. Proceedings of the 34th AAAI Conference on Artificial Intelligence: Student Abstract. 2020, 34(10): 13967-13968.


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Evolutionary Learning and Intelligent Optimization

Intelligent Evolutionary Algorithms

[2017]

[2017-1] Yuan Y, Ong Y S, Gupta A, et al. Objective Reduction in Many-Objective Optimization: Evolutionary Multiobjective Approach and Critical Analysis[J]. IEEE Transactions on Evolutionary Computation. 2017, 22(2): 189-210.


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[2016]

[2016-1] Yuan Y, Xu H, Wang B, et al. A New Dominance Relation Based Evolutionary Algorithm for Many-Objective Optimization[J]. IEEE Transactions on Evolutionary Computation. 2015, 20(1): 16-37.


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[2016-2] Yuan Y, Ong Y S, Gupta A, et al. Evolutionary Multitasking in Permutation-based Combinatorial Optimization Problems: Realization with TSP, QAP, LOP, and JSP[C]. Proceedings of the 14th IEEE Region 10 Conference. 2016: 3157-3164.


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[2015]

[2015-1] Yuan Y, Xu H, Wang B, et al. Balancing Convergence and Diversity in Decomposition-Based Many-Objective Optimizers[J]. IEEE Transactions on Evolutionary Computation. 2015, 20(2): 180-198.


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[2015-2] Yuan Y, Xu H, Wang B. An Experimental Investigation of Variation Operators in Reference-point based Many-objective Optimization[C]. Proceedings of the 17th Annual Conference on Genetic and Evolutionary Computation. 2015: 775-782.


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[2014]

[2014-1] Yuan Y, Xu H, Wang B. An Improved NSGA-III Procedure for Evolutionary Many-Objective Optimization[C]. Proceedings of the 16th Annual Conference on Genetic and Evolutionary Computation. 2014: 661-668.


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[2014-2] Yuan Y, Xu H, Wang B. Evolutionary Many-Objective Optimization Using Ensemble Fitness Ranking[C]. Proceedings of the 16th annual conference on genetic and evolutionary computation. 2014: 669-676.


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Flexible Job Shop Scheduling Problem Algorithm

[2015]

[2015-1] Yuan Y, Xu H. Multiobjective Flexible Job Shop Scheduling Using Memetic Algorithms[J]. IEEE Transactions on Automation Science and Engineering. 2015, 12(1): 336-353


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[2013]

[2013-1] Yuan Y, Xu H, Yang J. A Hybrid Harmony Search Algorithm for the Flexible Job Shop Scheduling Problem[J]. Applied soft computing. 2013, 13(7):3259-3272


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[2013-2] Yuan Y, Xu H. Flexible Job Shop Scheduling using Hybrid Differential Evolution Algorithms[J]. Computers & Industrial Engineering, 65(2):246-260


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[2013-3] Yuan Y, Xu H. An Integrated Search Heuristic for Large-scale Flexible Job Shop Scheduling Problems[J]. Computers & Operations Research, 2013, 40(12): 2864-2877.


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[2013-4] Yuan Y, Xu H. A Memetic Algorithm for the Multi-objective Job Shop Flexible Scheduling Problem[C]. Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation. 2013: 559-566.


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[2012]

[2012-1] Yuan Y, Xu H. HHS/LNS: An Integrated Search Method for Flexible Job Shop Scheduling[C]. Proceedings of the 2012 IEEE Congress on Evolutionary Computation. 2012: 1-8.


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Learning classifiers

[2013]

[2013-1] Yang J, Xu H, Jia P. Effective Search for Genetic-based Machine Learning Systems via Estimation of Distribution Algorithms and Embedded Feature Reduction Techniques[J]. Neurocomputing. 2013, 113: 105-121.


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[2013-2] Xu H, Yang J, Jia P, et al. Effective Structure Learning for Estimation of Distribution Algorithms via L1-Regularized Bayesian Networks[J]. International Journal of Advanced Robotic Systems. 2013, 10(1): 17.


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[2012]

[2012-1] Yang J, Xu H, Jia P. Effective Search for Pittsburgh Learning Classifier Systems via Estimation of Distribution Algorithms[J]. Information Sciences. 2012, 198: 100-117.


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[2012-2] Xu H, Wen Y, Wang J. A Fast-convergence Distributed Support Vector Machine in Small-scale Strongly Connected Networks[J]. Frontiers of Electrical and Electronic Engineering. 2012, 7(2): 216-223.


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[2011]

[2011-1] Wen Y, Xu H, Yang J. A Heuristic-based Hybrid Genetic-variable Neighborhood Search Algorithm for Task Scheduling in Heterogeneous Multiprocessor System[J]. Information Sciences. 2011, 181(3): 567-581.


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[2011-2] Yang J, Xu H, Pan L, et al. Task Scheduling using Bayesian Optimization Algorithm For Heterogeneous Computing Environments[J]. Applied Soft Computing. 2011, 11(4): 3297-3310.


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[2011-3] Wen Y, Xu H. A Cooperative Coevolution-based Pittsburgh Learning Classifier System Embedded with Memetic Feature Selection[C]. Proceedings of 13th IEEE Congress of Evolutionary Computation. 2011: 2415-2422.


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[2010]

[2010-1] Wen Y, Xu H, Yang J. A Heuristic-based Hybrid Genetic Algorithm for Heterogeneous Multiprocessor Scheduling[C]. Proceedings of the 12th annual conference on Genetic and evolutionary computation. 2010: 729-736.


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[2010-2] Yang J, Xu H, Cai Y, et al. Effective Structure Learning for EDA via L1-regularizedbayesian Networks[C]. Proceedings of the 12th annual conference on Genetic and evolutionary computation. 2010: 327-334.


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[2009]

[2009-1] Yang J, Xu H, Jia P. Task Scheduling for Heterogeneous Computing Based on Learning Classifier System[C]. Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence. 2009, 3: 370-374.


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Bayesian Optimization

[2023]

[2023-1] Wang H, Xu H, Zhang Z. High-Dimensional Multi-Objective Bayesian Optimization With Block Coordinate Updates: Case Studies in Intelligent Transportation System[J]. IEEE Transactions on Intelligent Transportation Systems, 2023.


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[2022]

[2022-1] Wang H, Xu H, Yuan Y. High-dimensional Expensive Multi-objective Optimization via Additive Structure[J]. Intelligent Systems with Applications. 2022, 14: 200062.


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[2022-2] Wang H, Xu H, Yuan Y, et al. An Adaptive Batch Bayesian Optimization Approach for Expensive Multi-Objective problems[J]. Information Sciences. 2022, 611: 446-463.


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[2019]

[2019-1] Wang H, Xu H, Yuan Y, et al. Balancing Exploration and Exploitation in Multiobjective Batch Bayesian Optimization[C]. Proceedings of the 33th Genetic and Evolutionary Computation Conference Companion. 2019: 237-238.


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[2019-2] Wang H, Xu H, Yuan Y, et al. Noisy Multiobjective Black-Box Optimization using Byesian Optimization[C]. Proceedings of the 33th Genetic and Evolutionary Computation Conference Companion. 2019: 239-240.


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Fast Large-Scale Optimization Algorithms

[2024]

[2024-1] Ye H, Xu H, Wang H, et al. Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Small-scale Optimizer and Small Training Dataset. Proceedings of the 12th International Conference on Learning Representations


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[2023]

[2023-1] Ye H, Xu H, Wang H, et al. GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming. The Fortieth International Conference on Machine Learning (ICML 2023).


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[2023-1] Ye H, Wang H, Xu H, et al. Adaptive Constraint Partition Based Optimization Framework for Large-scale Integer Linear Programming (student abstract)[C]. Proceedings of the AAAI Conference on Artificial Intelligence. 2023: 16376-16377.


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[2023-2] Chen L, Xu H, Wang Z, et al. Self-Paced learning based Graph Convolutional Neural Network for Mixed Integer Programming(Student Abstract)[C]. Proceedings of the AAAI Conference on Artificial Intelligence. 2023: 16188-16189.


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[2022]

[2022-1] Chen L, Xu H. MFENAS: Multifactorial Evolution for Neural Architecture Search[C]. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2022: 631-634.


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[2020]

[2020-1] Chen L, Xu H. CORAL-DMOEA: Correlation Alignment-Based Information Transfer for Dynamic Multi-Objective Optimization [C]. Proceedings of the 34th AAAI Conference on Artificial Intelligence: Student Abstract. 2020, 34(10): 13765-13766.


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Smart healthcare

[2023]

[2023-1] Xu H, Chen X, Qian P, et al. A Two-stage Segmentation of Sublingual Veins Based on Compact Fully Convolutional Networks for Traditional Chinese Medicine Images[J]. Health Information Science and Systems, 2023, 11(1): 19.


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[2022]

[2022-1] Mao H, Zhang B, Xu H, et al. An End-to-End Traditional Chinese Medicine Constitution Assessment System Based on Multimodal Clinical Feature Representation and Fusion[C]. Proceedings of the 36th AAAI Conference on Artificial Intelligence. 2022, 36(11): 13200-13202.


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[2022-2] Chen X, Xu H, Qian P, et al. Multi-kernel Convolutional Neural Network for Wrist Pulse Signal Classification[C]. Proceedings of the 32nd Conference of Open Innovations Association (FRUCT), 2022: 75-86.


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Demos and Datasets

Demos

[2023]

[2023-1] Mao H, Zhang B, Xu H, et al. Robust-MSA: Understanding the Impact of Modality Noise on Multimodal Sentiment Analysis[C]. Proceedings of the AAAI Conference on Artificial Intelligence. 2023: 16458-16460.


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[2022]

[2022-1] Mao H, Yuan Z, Xu H, et al. M-SENA: An Integrated Platform for Multimodal Sentiment Analysis[C]. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. 2022: 204-213.


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[2022-2]  Mao H, Zhang B, Xu H, et al. An End-to-End Traditional Chinese Medicine Constitution Assessment System Based on Multimodal Clinical Feature Representation and Fusion[C]. Proceedings of the 36th AAAI Conference on Artificial Intelligence: System Demonstrations. 2022: 13200 - 13202.


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[2022-3] Wu Z, Fang J, Xu H, et al. An In-depth Interactive and Visualized Platform for Evaluating and Analyzing MRC Models[C]. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 2022: 5044-5048.


[PDF]  [Code]

[2021]

[2021-1] Zhang H, Li X, Xu H, et al. TEXTOIR: An Integrated and Visualized Platform for Text Open Intent Recognition[C]. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations. 2021: 167–174.


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Datasets

Liu Y, Yuan Z, Mao H, et al. Make Acoustic and Visual Cues Matter: CH-SIMS v2. 0 Dataset and AV-Mixup Consistent Module[C]. Proceedings of the 24th International Conference on Multimodal Interaction. 2022: 247 - 258.


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Zhang H, Xu H, Wang X, et al. MIntRec: A New Dataset for Multimodal Intent Recognition[C]. Proceedings of the 30th ACM International Conference on Multimedia. 2022: 1688–1697.


[PDF]  [Code]

[2020-3] Yu W, Xu H, Meng F, et al. CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotations of Modality[C]. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020: 3718–3727.


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Monographs and Textbooks

Monographs

NaturalInteractionforTri-CoRobots(1)Human-machine Dialogue Intention Understanding (CN)


[Related Resources]

NaturalInteractionforTri-CoRobots(2)Human-machine Dialogue Intention Understanding (EN)


[Related Resources]

NaturalInteractionforTri-CoRobots(3)Sentiment Analysis of Multimodal Interaction Information


[Related Resources]

NaturalInteractionforTri-CoRobots(4)Named Entity Recognition and Information Extraction


[Related Resources]

Textbooks

Evolutionary Machine Learning


[Related Resources]

DataMining-Methodology and Applications


[Related Resources]

Data Mining-Methodology and Applications - Application Cases


[Cases Study]  [Related Resources]

Data Mining-Methodology and Applications(2ndedition)


[Related Resources]

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