Publications

• Recent Selected Publications

1. J. Xu, X. Tong, S.-L. Huang, "Personalized Federated Learning with Feature Alignment and Classifier Collaboration," In International Conference on Learning Representations (ICLR), 2023.

2. S.-L. Huang, A. Makur, G. W. Wornell, L. Zheng (2022). On Universal Features for High-Dimensional Learning and Inference. accepted to Foundations and Trends in Communications and Information Theory: Now Publishers. (ArXiv)

3. X. Xu, S.-L. Huang, “On Distributed Learning with Constant Communication Bits,” accepted to IEEE Journal on Selected Areas in Information Theory, 2021.

4. S.-L. Huang, X. Xu, “On The Sample Complexity of HGR Maximal Correlation Functions For Large Datasets,” IEEE Transactions on Information Theory, vol. 67, no. 3, pp. 1951-1980, March 2021. 

5. S.-L. Huang, X. Xu, L. Zheng, “An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data,” IEEE Journal on Selected Areas in Information Theory, vol. 1, no. 1, pp. 157–166, May 2020.

6. X. Tong, X. Xu, S.-L. Huang, L. Zheng, “A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning,” Thirty-fifth Conference on Neural Information Processing Systems (NIPS), 2021.

7. Z. Wang, S.-L. Huang, E. Kuruoglu, J. Sun, X. Chen, and Y. Zheng. PAC-Bayes Information Bottleneck. In International Conference on Learning Representations (ICLR), 2022.

8. X. Xu, S.-L. Huang, "On Distributed Hypothesis Testing with Constant-Bit Communication Constraints," IEEE Information Theory Workshop, Oct., 2021.

• Monograph

1. S.-L. Huang, A. Makur, G. W. Wornell, L. Zheng (2024), "Universal Features for High-Dimensional Learning and Inference", Foundations and Trends® in Communications and Information Theory: Vol. 21: No. 1-2, pp 1-299. http://dx.doi.org/10.1561/0100000107

• Journal Papers 

1. X. Tong, J. Xu, S.-L. Huang, "On the Fundamental Limit of Distributed Learning with Interchangable Constrained Statistics," submitted  (with minor revision) to IEEE Journal on Selected Areas in Information Theory, 2024

2. Y. Tan, E. Zhang, Y. Li, S.-L. Huang, X. Zhang, "Transferability-Guided Cross-Domain Cross-Task Transfer Learning," accepted to IEEE Transactions on Neural Networks and Learning Systems, 2024.

3. X. Tong, X. Xu, S.-L. Huang, "On the Optimal Error Exponent of Type-Based Distributed Hypothesis Testing," Entropy 2023, 25, 1434; https://doi.org/10.3390/e25101434

4. G. Yan, T. Li, S.-L. Huang, T. Lan, L. Song, “AC-SGD: Adaptively Compressed SGD for Communication-Efficient Distributed Learning,” IEEE Journal on Selected Areas in Communication, vol. 40, no. 9, pp. 2678-2693, Sep. 2022.

5. X. Xu, S.-L. Huang, “On Distributed Learning with Constant Communication Bits,” IEEE Journal on Selected Areas in Information Theory, vol. 3, no. 1, pp. 125-134, March 2022.

6. Z. Yang, Z. Pan, Y. Wang, D. Cai, S. Shi, S.-L. Huang, W. Bi, X. Liu, "Interpretable Real-Time Win Prediction for Honor of Kings—A Popular Mobile MOBA Esport," IEEE Transactions on Games, vol. 14, pp. 589 - 597, Dec. 2022. 

7. F. Zhao, S.-L. Huang, "On the Universally Optimal Activation Function for a Class of Residual Neural Networks." AppliedMath 2022, 2, 574-584.

8. S.-L. Huang, X. Xu, L. Zheng, G. W. Wornell, “An Information Theoretic Interpretation to Deep Neural Networks,” Entropy 2022, 24(1), 135; https://doi.org/10.3390/e24010135

9. F. Ma, Y. Li, S. Ni, S.-L. Huang, L. Zhang, “Data Augmentation for Audio-Visual Emotion Recognition with an Efficient Multimodal Conditional GAN,” Applied Sciences 12, no. 1: 527, 2022.

10. S.-L. Huang, X. Xu, “On The Sample Complexity of HGR Maximal Correlation Functions For Large Datasets,” IEEE Transactions on Information Theory, vol. 67, no. 3, pp. 1951-1980, March 2021. 

11. F. Zhao, M. Ye, S.-L. Huang, “Exact Recovery of Stochastic Block Model by Ising Model,” Entropy 2021, 23, 65.

12. S.-L. Huang, X. Xu, L. Zheng, “An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data,” IEEE Journal on Selected Areas in Information Theory, vol. 1, no. 1, pp. 157–166, May 2020.

13. F. Ma, W. Zhang, Y. Li, S.-L. Huang, L. Zhang, “Learning Better Representations for Audio-Visual Emotion Recognition,” Applied Sciences, doi: 10.3390, 2020.

14. X. Xu, S.-L. Huang, “On the Optimal Tradeoff between Computational Efficiency and Generalizability of Oja’s Algorithm,” IEEE Access, 2020, 8: 102616-102628.

15. X. Xu and S.-L. Huang, “Maximal Correlation Regression,” IEEE Access, 2020, 8: 26591-26601.

16. J. Lian, Y. Li, W. Gu, S.-L. Huang, L. Zhang, “Mining Regional Mobility Patterns for Urban Dynamic Analytics,” Mobile Networks and Applications (2019): 1-15.

17. S. Zhang, Y. Dong, H. Fu, S.-L. Huang, L. Zhang, “A Spectral Reconstruction Algorithm of Miniature Spectrometer Based on Sparse Optimization and Dictionary Learning,” Sensors (Basel). 2018 Feb. 22. 

18. K.-C. Chen, S.-L. Huang, L. Zheng, H. V. Poor, “Communication Theoretic Data Analytics,” IEEE Journal on Selected Areas in Communications, vol. 33, no. 4, pp. 663-675, April 2015. 

19. S.-L. Huang, C. Suh, L. Zheng, “Euclidean Information Theory of Networks,” IEEE transactions on Information Theory, vol. 61, pp. 6795-6814, Dec. 2015. 

20. E. Abbe, S.-L. Huang, E. Telatar, “Proof of the outage probability conjecture for MISO channels,” IEEE transactions on Information Theory, vol. 59, pp. 2596- 2602, May 2013. 

• Conference Papers 

1.  X. Liang, T. Shi, Y. Liang, T. Tao, S.-L. Huang, "Exploring Iterative Refinement with Diffusion Models for Video Grounding," IEEE International Conference on Multimedia and Expo (ICME), Jul., 2024.

2.  X. Yang, H. Song, X. Lu, S.-L. Huang, Y. Duan, "AdaForensics: Learning A Characteristic-aware Adaptive Deepfake Detector," IEEE International Conference on Multimedia and Expo (ICME), Jul., 2024.

3. X. Yu, S. Wei, S.-L. Huang, X. Zhang, "On The Second Order Asymptotics of Covert Communications over AWGN Channels," IEEE International Conference on Communications (ICC), June, 2024.

4. Y. Li, H. Huang, J. Xu, S.-L. Huang, "NAC: Mitigating Noisy Correspondence in Cross-Modal Matching via Neighbor Auxiliary Corrector," IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Apr., 2024.

5. Y. Liang, X. Liang, Y. Tang, Z. Yang, Z. Li, J. Wang, W. Ding, S.-L. Huang, “CoSTA: End-to-End Comprehensive Space-Time Entanglement for Spatio-Temporal Video Grounding,” Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), Feb., 2024.

6. J. Liu, Y. Wang, S.-L. Huang, D. Sun, "Risk Sensitive Distributional Soft Actor Critic for Portfolio Management," International Conference on Big Data Analytics, Mar., 2024.

7. J. Xu, G. Yan, Z. Zheng, S.-L. Huang, "Mitigating Model Poisoning Attacks on Distributed Learning with Heterogeneous Data," 22nd IEEE International Conference on Machine Learning and Applications (ICMLA), Dec., 2023.

8. J. Xu, S.-L. Huang, "A Joint Training-Calibration Framework for Test-Time Personalization with Label Shift in Federated Learning," ACM International Conference on Information and Knowledge Management (CIKM), Oct., 2023.

9. X. Tong, S.-L. Huang, "Optimal Error Exponent of Type-Based Distributed Hypothesis Testing over AWGN Channels," Allerton Annual Conference on Communication, Control and Computing, Sep. 2023.

10. X. Tong, X. Xu, S.-L. Huang, L. Zheng, "Robust Transfer Learning Based on Minimax Principle," Allerton Annual Conference on Communication, Control and Computing, Sep. 2023.

11. W. Wang, X. Yu, X. Tong, R. Yu, S.-L. Huang, X. Zhang, "Robust Deep Joint Source Channel Coding with Time-varying Noise," IEEE Global Communications Conference, Dec., 2023.

12. Y. Liang, Z. Yang, Y. Tang, J. Fan, Z. Li, J. Wang, P. Torr, S.-L. Huang, "LUNA: Language as Continuing Anchors for Referring Expression Comprehension", In ACM International Conference on Multimedia (ACM MM), 2023.

13. J. Fan, Y. Liang, L. Liu, S.-L. Huang, L. Zhang, “RCA-NOC: Relative Contrastive Alignment for Novel Object Captioning,” International Conference on Computer Vision (ICCV), 2023.

14. X. Tong, S.-L. Huang, "An Information Theoretic Approach for Collaborative Distributed Parameter Estimation," IEEE International Symposium on Information Theory (ISIT), June, 2023.

15. J. Xu, X. Tong, S.-L. Huang, "Personalized Federated Learning with Feature Alignment and Classifier Collaboration," In International Conference on Learning Representations (ICLR), 2023.

16. X. Dai, M. Li, P. Zhai, S. Tong, X. Gao, S.-L. Huang, Z. Zhu, C. You, Y. Ma, "Revisiting Sparse Convolutional Model for Visual Recognition," Thirty-Sixth Conference on Neural Information Processing Systems (NIPS), 2022.

17. X. Tong, X. Xu, S.-L. Huang, "On Sample Complexity of Learning Shared Representations: The Asymptotic Regime," Allerton Annual Conference on Communication, Control and Computing, Sep. 2022. 

18. S.-L. Huang, "Communicating Type Classes Through Channels: An Information Geometric View," IEEE Information Theory Workshop, Nov., 2022.

19. X. Tong, J. Xu, S.-L. Huang, "An Information-theoretic Method for Collaborative Distributed Learning with Limited Communication," IEEE Information Theory Workshop, Nov., 2022.

20. J. Xu, Y. Yan, S.-L. Huang, "FedPer++: Toward Improved Personalized Federated Learning on Heterogeneous and Imbalanced Data," in IEEE International Joint Conference on Neural Network (IJCNN), 2022.

21. J. Xu, S.-L. Huang, L. Song, and T. Lan, "Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering," in IEEE International Conference on Distributed Computing Systems (ICDCS), 2022.

22. T. Peng, W. Wang, S.-L. Huang, "A Mathematical Framework to Characterize the Dependency Structures in Multimodal Learning With Minimax Principle," IEEE International Symposium on Information Theory (ISIT), June, 2022.

23. Z. An, Z. Wu, B. Hu, Z. Zhang, J. Zhou, Y. Wang, S.-L. Huang, "Decoupled Graph Neural Networks based on Label Agreement Message Propagation," ICLR Workshop on Geometrical and Topological Representation Learning, 2022.

24. J. Xu, S.-L. Huang, "Byzantine-Resilient Decentralized Collaborative Learning," IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May, 2022.

25. M. Li, S.-L. Huang, L. Zhang, "A General Framework For Incomplete Cross-modal Retrieval With Missing Labels And Missing Modalities", IEEE International Conference on Acoustics, Speech, and Signal Processing, May, 2022.

26. Z. Wang, S.-L. Huang, E. Kuruoglu, J. Sun, X. Chen, and Y. Zheng. PAC-Bayes Information Bottleneck. In International Conference on Learning Representations (ICLR), 2022.

27. Z. Zheng, X. Tong, X. Yu, X. Xu, S.-L. Huang, "Multi-source Transfer Learning for Signal Detection over a Fading Channel with Co-channel Interference," IEEE International Conference on Communications (ICC), May, 2022.

28. J. Xu, X. Tong, S.-L. Huang, "Communication-Efficient and Byzantine-Robust Distributed Stochastic Learning with Arbitrary Number of Corrupted Workers," IEEE International Conference on Communications (ICC), May, 2022.

29. R. Yu, H. Zhu, K. Li, L. Hong, R. Zhang, N. Ye, S.-L. Huang, X. He ”Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms,” Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), Feb., 2022.

30. X. Tong, X. Xu, S.-L. Huang, L. Zheng, “A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning,” Thirty-fifth Conference on Neural Information Processing Systems (NIPS), 2021.

31. B. Eua-arporn, S.-L. Huang, E. Kuruoglu, “Enhancing Neural Network Based Hybrid Learning with Empirical Wavelet Transform for Time Series Forecasting,” 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI).

32. G. Yan, S.-L. Huang, T. Lan, L. Song, "DQ-SGD: Dynamic Quantization in SGD for Communication-Efficient Distributed Learning," 2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS)

33. X. Xu, S.-L. Huang, "On Distributed Hypothesis Testing with Constant-Bit Communication Constraints," IEEE Information Theory Workshop, Oct., 2021.

34. J. Sima, F. Zhao, S.-L. Huang, "Exact Recovery in the Balanced Stochastic Block Model with Side Information," IEEE Information Theory Workshop, Oct., 2021.

35. F. Zhao, J. Sima, S.-L. Huang, "On the Optimal Error Rate of Stochastic Block Model with Symmetric Side Information," IEEE Information Theory Workshop, Oct., 2021.

36. J. Li, Z. Wang, Z. Zhao, Y. Jin, J. Yin, S.-L. Huang, J. Wang, “TriboGait: A Deep Learning Enabled Triboelectric Gait Sensor System for Human Activity Recognition and Individual Identification,” in Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers (UbiComp/ISWC), Sep., 2021.

37. M. Li, S.-L. Huang, L. Zhang, “OTCMR: Bridging Heterogeneity Gap with Optimal Transport for Cross-modal Retrieval”, 30th ACM International Conference on Information and Knowledge Management (CIKM), 2021.

38. M. Li, X. Xu, S.-L. Huang, L. Zhang, “Dual Feature Distributional Regularization for Defending against Adversarial Attacks”, 28th International Conference on Neural Information Processing (ICONIP), 2021.

39. Z. Wang, Y. Yang, R. Wen, X. Chen, S.-L. Huang, Y, Zheng, "Lifelong Learning based Disease Diagnosis on Clinical Notes," 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2021), May, 2021, Delhi, India. (Best student paper)

40. X. Xu and S.-L. Huang, “An Information Theoretic Framework for Distributed Learning Algorithms,” IEEE International Symposium on Information Theory (ISIT), July, 2021.

41. S. Yin, F. Ma, S.-L. Huang, "A Semi-supervised Learning Approach for Visual Question Answering based on Maximal Correlation," 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

42. F. Ma, S.-L. Huang, L. Zhang, "An Efficient Approach for Audio-Visual Emotion Recognition with Missing Labels and Missing Modalities," IEEE International Conference on Multimedia and Expo (ICME), Jul., 2021. 

43.  Y. Tan, Y. Li, S.-L. Huang. "OTCE: A Transferability Metric for Cross-Domain Cross-Task Representations," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun., 2021.

44. W. Sun, F. Ma, Y. Li, S.-L. Huang, S. Ni, L. Zhang, "Semi-Supervised Multimodal Image Translation for Missing Modality Imputation", IEEE International Conference on Acoustics, Speech, and Signal Processing, June, 2021.

45. J. Xu, S.-L. Huang, L. Song, T. Lan, “Live Gradient Compensation for Evading Stragglers in Distributed Learning,” IEEE International Conference on Computer Communications, May, 2021.

46. Y. Liang, F. Ma, Y. Li, S.-L. Huang “Person Recognition with HGR Maximal Correlation on Multimodal Data” IEEE International Conference on Pattern Recognition (ICPR), Jan., 2021.

47. Z. Wang, X. Chen, R. Wen, S.-L. Huang, E. Kuruoglu, Y. Zheng, “Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback,” Thirty-fourth Conference on Neural Information Processing Systems (NIPS), 2020.

48. M. Li, Y. Li, S.-L. Huang, L. Zhang, “Semantically Supervised Maximal Correlation For Cross-Modal Retrival” IEEE International Conference on Image Processing (ICIP), Oct., 2020.

49. X. Xu, W. Wang, S.-L. Huang, “On the Sample Complexity of Estimating Small Singular Modes” IEEE International Symposium on Information Theory, June, 2020.

50. S.-L. Huang, X. Xu, L. Zheng, G. W. Wornell, “A Local Characterization for Wyner Common Information,” IEEE International Symposium on Information Theory, June, 2020.

51. Z. Wang, H. Zhu, Z. Dong, X. He, S.-L. Huang, ”Less is better: Unweighted Data Subsampling via Influence Function,” Proceedings of the 34rd AAAI Conference on Artificial Intelligence (AAAI-20), Feb., 2020. 

52. F. Zhao, F. Ma, Y. Li, S.-L. Huang, L. Zhang, ”Info-detection: An information-theoretic approach to detect outlier.” 2019-26th International Conference on Neural Information Processing (ICONIP). 

53. X. Xu, S.-L. Huang, “On the Asymptotic Sample Complexity of HGR Maximal Correlation Functions in Semi-supervised Learning,” Allerton Annual Conference on Communication, Control and Computing, Sep. 2019. 

54. J. Lian, Y. Li, S.-L. Huang, L. Zhang, “Mining Mobility Patterns with Trip- Based Traffic Analysis Zones: A Deep Feature Embedding Approach.” accepted by 2019 IEEE 22nd International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2019. 

55. S.-L. Huang, X. Xu, “On The Sample Complexity of HGR Maximal Correlation Functions,” IEEE Information Theory Workshop, Aug., 2019. 

56. M. Li, H. Wang, S.-L. Huang, L. Zhang, “ Anomaly Detection in Surface Mount Technology Process using Multi-modal Data,” Proceedings of the 17th ACM Conference on Embedded Networked Sensor Systems, Nov., 2019. 

57. Y. Bao, Y. Li, S.-L. Huang, L. Zhang, L. Zheng, A. Zamir, L. Guibas “An Information-Theoretic Approach To Transferability In Task Transfer Learning” IEEE International Conference on Image Processing (ICIP), Sep., 2019. 

58. S.-L. Huang, X. Xu, “On the Robustness of Noisy ACE Algorithm and Multi-Layer Residual Learning,” IEEE International Symposium on Information Theory, Jul., 2019. 

59. S.-L. Huang, X. Xu, L. Zheng, G. W. Wornell, “An Information Theoretic Interpretation to Deep Neural Networks,” IEEE International Symposium on Information Theory, Jul., 2019. 

60. F. Ma, W. Zhang, Y. Li, S.-L. Huang, L. Zhang, “ An End-to-end Learning Approach For Multimodal Emotion Recognition: Extracting Common and Private Information,” IEEE International Conference on Multimedia and Expo (ICME), Jul., 2019. 

61. L. Li, X. Xu, Y. Li, S.-L. Huang, L. Zhang, “ Maximal Correlation Embedding Network for Multi-label Learning with Missing Labels,” IEEE International Conference on Multimedia and Expo (ICME), Jul., 2019. 

62. L. Wang, J. Wu, S.-L. Huang, L. Zheng, X. Xu, L. Zhang, J. Huang, “An Efficient Approach to Informative Feature Extraction from Multimodal Data,” Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19), Jan., 2019. 

63. H. Wang, M. Li, F. Ma, S.-L. Huang, L. Zhang, “ Unsupervised anomaly detection via generative adversarial networks,” Proceedings of the 18th International Conference on Information Processing in Sensor Networks, Apr., 2019. 

64. J. Lian, Y. Li, W. Gu, S.-L. Huang, L. Zhang, “Joint Mobility Pattern Mining with Urban Region Partitions,” Proceedings of the 15th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, Nov., 2018. (Best paper award) 

65. F. Ma, W. Gu, W. Zhang, S. Ni, S.-L. Huang, L. Zhang, “ Speech Emotion Recognition via Attention-based DNN from Multi-Task Learning,” Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems, Nov., 2018. 

66. Q. Du, W. Gu, L. Zhang, S.-L. Huang, “ Attention-based LSTM-CNNs For Time- series Classification,” Proceedings of the 16th ACM Conference on Embedded Net- worked Sensor Systems, Nov., 2018. 

67. X. Xu, S.-L. Huang, L. Zheng, and L. Zhang. “The Geometric Structure of Generalized Softmax Learning,” 2018 IEEE Information Theory Workshop, Nov., 2018. 

68. S.-L. Huang, L. Zheng, G. Wornell, “Gaussian Universal Features, Canonical Correlations, and Common Information,” IEEE Information Theory Workshop, Nov., 2018. 

69. S.-L. Huang, L. Zhang, L. Zheng, “An information-theoretic approach to unsupervised feature selection for high-dimensional data,” IEEE Information Theory Workshop, Nov., 2017. 

70. S.-L. Huang, A. Makur, L. Zheng, G. W. Wornell, “An Information-Theoretic Approach to Universal Feature Selection in High-Dimensional Inference,” IEEE International Symposium on Information Theory, June, 2017. 

71. I-H. Wang, S.-L. Huang, K.-Y. Lee, “Extracting Sparse Data via Histogram Queries,” Allerton Annual Conference on Communication, Control and Computing, October 2016. 

72. I-H. Wang, S.-L. Huang, K.-Y. Lee, “Data Extraction via Histogram and Arithmetic Mean Queries: Fundamental Limits and Algorithms,” IEEE International Symposium on Information Theory, June, 2016. 

73. A. Makur, F. Kozynski, S.-L. Huang, L. Zheng, “Parallel ACE Algorithm: An Efficient Algorithm to Extract Non-Linear Features from High Dimensional Data,” Allerton Annual Conference on Communication, Control and Computing, October 2015. 

74. S.-L. Huang, L. Zheng, “A Spectrum Decomposition to the Feature Spaces and the Application to Big Data Analytics,” IEEE International Symposium on Information Theory, June, 2015. 

75. A. Makhdoumi, S.-L. Huang, Y. Polyanskiy, M. Medard, “On Locally Decodable Source Coding,” IEEE International Conference on Communications, June, 2015. 

76. S.-L. Huang, K.-C. Chen, “Information Cascades in Social Networks via Dynamic System Analyses,” IEEE International Conference on Communications, June, 2015. 

77. S.-L. Huang, A. Makur, F. Kozynski, and L. Zheng, “Efficient Statistics: Extracting Information from IID Observations,” Allerton Annual Conference on Communication, Control and Computing, Oct., 2014. 

78. K.-H., Peng, K.-C. Chen, S.-L. Huang, “Green Traffic Compression in Wireless Sensor Networks,” IEEE 79th Vehicular Technology Conference, May, 2014. 

79. S.-L. Huang, C. Suh, L. Zheng, “Euclidean Information Theory of Networks,” IEEE International Symposium on Information Theory, July, 2013. 

80. S.-L. Huang, L. Zheng, “Linear Information Coupling Problems,” IEEE International Symposium on Information Theory, July, 2012. 

81. E. Abbe, S.-L. Huang, E. Telatar, “Proof of the outage probability conjecture for MISO channels,” IEEE Information Theory Workshop, Sep., 2012. 

82. S.-L. Huang, Y. Blankenship, and L. Zheng, “The design of binary shaping filter of binary code,” IEEE Wireless Communications, Networking and Information Security, pp. 228-232, June, 2010.