Publications


NLP

  1. F. Tan, Y. Hu, C. Hu, K. Li, K. Yen. TNT: Text Normalization based Pre-training of Transformers for Content Moderation, EMNLP 2020. [PDF]
  2. T. Tran, Y. Hu, C. Hu, K. Yen, F. Tan, K. Lee, S. Park. HABERTOR: An Efficient and Effective Deep Hatespeech Detector, EMNLP 2020. [PDF]
  3. B. An, J. Lyu, Z. Wang, C. Li, C. Hu, F. Tan, R. Zhang, Y. Hu, C. Chen. Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference, EMNLP 2020. [PDF]
  4. C. Hu, S. Mishra, K. Yen, Y. Hu, M Sviridenko. Creative Assistant: BERT based Ad Text Analyzer, Techpulse 2020. ( Selected as talk )
  5. T. Tran, Y. Hu, C. Hu, K. Yen, F. Tan, K. Li. Efficient Hyper-parameter Optimization for Neural Networks, Techpulse 2020.
  6. F. Tan, Y. Hu, K. Yen, C. Hu, K. Li. Text Normalization for Combating Misspells, Techpulse 2020.
  7. F. Tan, C. Hu, Y. Hu, K. Yen, K. Li. MGEL: Multi-Grained Text Representation Analysis and Ensemble Learning in Online Abusive Language Detection, Techpulse 2020.
  8. F. Tan, Y. Hu, C. Hu, K. Li, K. Yen. TNT: Text Normalization based Pre-training of Transformers for Language Understanding, Techpulse 2020.
  9. Y. Hu, C. Hu, T. Tran, T. Kasturi, E. Joseph, I. Selinger. Gender Classification Using Full Names and Content, Techpulse 2020.
  10. C. Hu, K. Yen, Y. Hu, M. Dinh, M. Choe, D. Matheson, M. Chen. Summarize Topics of User Comments for Editorial Board, Techpulse 2020.
  11. T. Tran, Y. Hu, C. Hu, K. Yen, F. Tan, K. Lee, K. Li, S. Park. HABERTOR: An Efficient and Effective Deep Hatespeech Detector, Techpulse 2020.
  12. Y. Zhang, C. Hu, Y. Hu, T. Kasturi, M. Gillingham, S. Ramasamy, K. Yamamoto. Large-scale Gender/Age Prediction of Tumblr Users, IEEE International Conference on Machine Learning and Applications (ICMLA) 2019, Boca Raton, Florida, US. [PDF]
  13. Y. Hu, C. Hu, K. yen, S. Park, F. Tan, T. Kasturi, A. Kamat, A. Chowdhury. Improving Hate Speech Detection in User Comments, Techpulse 2019, California, US. ( Selected as talk )
  14. Y. Hu, C. Hu, T. Tran, T. Kasturi, E. Joseph, M. Gillingham. What’s in a Name? – Gender Classification of Names with Character Based Machine Learning Models, Techpulse 2019, California, US. ( Selected as talk )
  15. T. Tran, Y. Hu, C. Hu, K. Yen, F. Tan, S. Park. Language Model for Hate-speech Classification in Yahoo News and Finance, Techpulse 2019, California, US. ( Selected as talk )
  16. S. Park, K. Yen, Y. Hu, C. Hu, S. Subramanya. New Hate Speech Classification Service for Verizon Media, Techpulse 2019, California, US. ( Selected as talk )
  17. Y. Zhang, C. Hu, S. Ramasamy, M. Gillingham, Y. Hu, T. Kasturi, K. Yamamoto. Large-scale Gender and Age Prediction for Sponsored Ad Targeting for Tumblr Users, Techpulse 2018, California, US.
  18. Y Zhang, C Hu, Y Hu, T Kasturi. Improving Tumblr Demographic Ad Targeting, Techpulse 2017, California, US.
  19. C Hu, P Rai, L Carin. Deep Generative Models for Relational Data with Side Information, ICML 2017, Sydney, Australia. [PDF]
  20. C Hu, P Rai, L Carin. Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information, AISTATS 2016, Cadiz, Spain. [PDF] [Code]
  21. C Hu, P Rai, L Carin. Topic-Based Embeddings for Learning from Large Knowledge Graphs, AISTATS 2016, Cadiz, Spain. [PDF] [supp] [Code]
  22. C Hu, P Rai, L Carin. Transfer Learning for Hierarchically Supervised Topic Models, 2015 NIPS Workshop in Transfer and Multi-task Learning, Montreal, Canada. [PDF]
  23. P Rai, C Hu, R Henao, L Carin. Scalable Bayesian Non-Negative Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings, NIPS 2015, Montreal, Canada. (Spotlight Presentation ) [PDF] [Code]
  24. C Hu, P Rai, C Chen, M Harding, L Carin. Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data, ECML-PKDD 2015, Porto, Portugal. [PDF] [arXiv] [Code] (Best Student Paper Award )
  25. C Hu, P Rai, L Carin. Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors, UAI 2015, Amsterdam, The Netherlands. [PDF] [arXiv] [Code] (Plenary Oral Presentation )
  26. P Rai, C Hu, R Henao, L Carin. Large-scale Bayesian Multi-label Learning via Positive Labels Only, ICML workshop 2015, Lille, France.
  27. P Rai, C Hu, M Harding, L Carin. Scalable Probabilistic Tensor Factorization for Binary and Count Data, IJCAI 2015, Buenos Aires, Argentina. [PDF]
  28. C Hu, E Ryu, D Carlson, Y Wang, L Carin. Latent Gaussian Models for Topic Modeling, AISTATS 2014, Reykjavik, Iceland. [PDF]

    29. Time Series Analysis

  29. M. Verma, D. Manickam, Y. Hu, C. Hu, A. Gupta. Time series prediction and anomaly detection in Monitoring platforms, Techpulse 2020. ( Selected as talk )
  30. C. Hu, Y. Hu, S. Seo. A Deep Structural Model for Analyzing Correlated Multivariate Time Series, IEEE International Conference on Machine Learning and Applications (ICMLA) 2019, Boca Raton, Florida, US. [PDF]
  31. M. Verma, Y. Hu, C. Hu, T. Kasturi, P. Silva, P. Thairu. AWS Billing Costs Anomaly Detection, Techpulse 2019, California, US.
  32. C. Hu, S. Seo, Y. Hu, T. Kasturi, P. Thairu. A Deep Multivariate Structural Time Series Model for Oath’s AWS Billing Forecasting, Techpulse 2018, California, US. ( Selected talk for the Science track )

    33. Computer Vision

  33. B Ning, X Qu, D Guo, C Hu, Z Chen. Magnetic Resonance Image Reconstruction using Trained Geometric Directions in 2D Redundant Wavelets Domain and Non-convex Optimization, Magnetic Resonance Imaging, 31(9):1611-1622, 2013. [PDF]
  34. Z Chen, C Hu, X Qu, L Bao, S Cai. Improving Edge Recovery in Undersampled MRI Reconstruction, International Society for Magnetic Resonance in Medicine 20th Scientific Meeting 2012, Melbourne, Australia. (abstract)
  35. C Hu, X Qu, D Guo, L Bao, Z Chen. Wavelet-based Edge Correlation Incorporated Iterative Reconstruction for Undersampled MRI, Magnetic Resonance Imaging, 31(9):1611-1622, 2011. [PDF]
  36. C Hu, X Qu, D Guo, L Bao, S Cai, Z Chen. Undersampled MRI Reconstruction using Edge-weighted L1 Norm Minimization, International Society for Magnetic Resonance in Medicine 19th Scientific Meeting 2011, Montreal, Canada. (abstract)
  37. Lijun Bao, Wanyu Liu, Changwei Hu, Xiaobo Qu, Shuhui Cai, Zhong Chen. Three Dimensional Restoration of Cardiac Magnetic Resonance Diffusion Weighted Images based on Sparse Denoising, International Society for Magnetic Resonance in Medicine 19th Scientific Meeting 2011, Montreal, Canada. (abstract)
  38. X Qu, C Hu, D Guo, L Bao, Z Chen.Gaussian Scale Mixture-based Joint Reconstruction of Multicomponent MR Images from Undersampled k-space Measurements, International Society for Magnetic Resonance in Medicine 19th Scientific Meeting 2011, Montreal, Canada. (abstract)
  39. X Qu, X Cao, D Guo, C Hu, Z Chen. Compressed Sensing MRI with Combined Sparsifying Transforms and Smoothed l0 Norm Minimization, ICASSP 2010, Dallas, Texas. [PDF]
  40. X Qu, X Cao, D Guo, C Hu, Z Chen. Combined Sparsifying Transforms for Compressed Sensing MRI, Electronics Letters 46 (2), 121-123, 2010. [PDF]
  41. X Qu, C Hu, J Yan. Image Fusion Algorithm based on Orientation Information Motivated Pulse Coupled Neural Networks, 7th World Congress on Intelligent Control and Automation 2008, Chongqing, China. [PDF]

    42. Other: Fraud Detection, Computational Phenotyping, etc

  42. K. Yen, N. Petikyan, A Bhardwaj, G Mehta, C. Hu, K. Li, Y. Hu. Improving Human Review Efficiency With Machine Learning Models, Techpulse 2020.
  43. C. Hu, Y. Hu, T. Kasturi, S. Mayasula, K. Sriram, A. Jayakumar, B. Muttineni. Improving Payments Fraud Detection: Unifying Machine Learning and Visualization, Techpulse 2019, California, US.
  44. C Hu, R Henao, T Frank, S Bhardwaj, P Rai, L Carin. Computational Phenotyping via Scalable Bayesian Tensor Factorization, 2015 NIPS Workshop on Machine Learning in Healthcare, Montreal, Canada. [PDF]