Publications

    2025

  1. [DAC] G. Sun*, L. Chen*, Q. Huang, H. Ding, "To Tackle Cost-Skew Tradeoff: An Adaptive Learning Approach for Hub Node Selection", to appear in the 62nd Design Automation Conference(DAC'62) (the first two authors are both first authors).
  2. [ICLR] S. Song*, G. Mo*, H. Ding, "Relax and Merge: A Simple Yet Effective Framework for Solving Fair k-Means and k-sparse Wasserstein Barycenter Problems", to appear in The Thirteenth International Conference on Learning Representations (ICLR'25) (the first two authors are both first authors).
  3. [ICLR] W. Zhang, W. Lin, R. Huang, S. Song, H. Ding, "To Tackle Adversarial Transferability: A Novel Ensemble Training Method with Fourier Transformation", to appear in The Thirteenth International Conference on Learning Representations (ICLR'25).
  4. [ICLR] X. Wang, H. Ding, "Exploring The Forgetting in Adversarial Training: A Novel Method for Enhancing Robustness", to appear in The Thirteenth International Conference on Learning Representations (ICLR'25).
  5. [ICLR] J. Huang, H. Ding, "An Effective Manifold-based Optimization Method for Distributionally Robust Classification", to appear in The Thirteenth International Conference on Learning Representations (ICLR'25).
  6. [CommsChem] P. Hua*, Z. Huang*, Z. Xu*, Q. Zhao, C. Ye, Y. Wang, Y. Xu, Y. Fu, H. Ding, "An Active Representation Learning Method for Reaction Yield Prediction with Small-scale Data", to appear in Communications Chemistry (the first three authors are all first authors).

    7. 2024

  7. [ACM MM] Q. Chen, W. Liu, H. Ding，"A Novel Confidence Guided Training Method for Conditional GANs with Auxiliary Classifier", in ACM Multimedia (ACM MM'24).
  8. [COCOON] J. Huang, W. Liu, H. Ding, “Bi-criteria Sublinear Time Algorithms for Clustering with Outliers in High Dimensions”, in International Computing and Combinatorics Conference (COCOON 2024).
  9. [ICML] W. Lin*, J. Chen*, R. Huang, H. Ding, “An Effective Dynamic Gradient Calibration Method for Continual Learning”, in International Conference on Machine Learning (ICML'24) (the first two authors are both first authors).
  10. [IJCAI] Q. Yang, H. Ding, “Approximate Algorithms For k-Sparse Wasserstein Barycenter With Outliers”, in the International Joint Conference on Artificial Intelligence (IJCAI'24).
  11. [SIGMOD] G. Mo, S. Song, H. Ding, “Towards Metric DBSCAN: Exact, Approximate, and Streaming Algorithms”, in The 2024 ACM SIGMOD International Conference on Management of Data (SIGMOD'24).
  12. [DAC] L. Chen, Q. Xu, H. Ding, “OTPlace-Vias: A Novel Optimal Transport Based Method for High Density Vias Placement in 3D Circuits”, in The 61st Design Automation Conference (DAC'24).
  13. [AAAI] X. Xu, H. Ding, “A Novel Skip Orthogonal List for Dynamic Optimal Transport Problem”, in The 38rd AAAI Conference on Artificial Intelligence (AAAI'24).

    2023

  14. [ICCAD] L. Yang, G. Sun, H. Ding, “Towards Timing-Driven Routing: An Efficient Learning Based Geometric Approach”, in 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD). IEEE, 2023: 1-9.
  15. [MICCAI] W. Liu, H. Ding, “Solving Low-Dose CT Reconstruction via GAN with Local Coherence”, in International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer Nature Switzerland, 2023: 524-534.
  16. [JEA] H. Ding, W. Liu, M. Ye, "A Data-dependent Approach for High-dimensional (Robust) Wasserstein Alignment", in ACM Journal of Experimental Algorithmics 28 (2023): 1-32.

    2022

  17. [NeurIPS] R. Huang, J. Huang, W. Liu, H. Ding, “Coresets for Wasserstein Distributionally Robust Optimization Problems”, in NeurIPS 2022 (spotlight, acceptance rate<=3%).
  18. [NeurIPS] J. Chen, Q. Yang, R. Huang, H. Ding, “Coresets for Relational Data and The Applications”, in NeurIPS 2022 (spotlight, acceptance rate<=3%).
  19. [UAI] Q. Chen*, K. Liu*, R. Yao, H. Ding, “Sublinear Time Algorithms for Greedy Selection in High Dimensions”, in 387th Conference on Uncertainty in Artificial Intelligence (UAI'22) (the first two authors are both first authors).
  20. [IJCGA] J. Huang, R. Qin, F. Yang, H. Ding, “Random Projection and Recovery for High Dimensional Optimization with Arbitrary Outliers”, in Int. J. Comput. Geom. Appl. (IJCGA).

    2021

  21. [NeurIPS] Z. Wang, Y. Guo, H. Ding, "Robust and Fully-Dynamic Coreset for Continuous-and-Bounded Learning (With Outliers) Problems", NeurIPS 2021: 14319-14331 (spotlight, acceptance rate<=3%).
  22. [NeurIPS] R. Qin, M. Li, H. Ding, "Solving Soft Clustering Ensemble via k-Sparse Discrete Wasserstein Barycenter", NeurIPS 2021: 900-913.
  23. [ESA]   H. Ding, "Stability Yields Sublinear Time Algorithms for Geometric Optimization in Machine Learning", in the 29th European Symposium on Algorithms (ESA'21): 38:1-38:19.
  24. [ICML]   J. Huang*, R. Huang*, W. Liu*, N. Freris, H. Ding , "A Novel Sequential Coreset Method for Gradient Descent Algorithms, " in International Conference on Machine Learning (ICML'21): 4412-4422. (the first three authors are all first authors)
  25. [UAI]   H. Ding, F. Yang, J. Huang, "Defending SVMs Against Poisoning Attacks: The Hardness and DBSCAN Approach", in 37th Conference on Uncertainty in Artificial Intelligence (UAI'21).
  26. [SDM]   H. Ding, T. Chen, F. Yang, M. Wang, "A Data-Dependent Algorithm for Querying Earth Mover's Distance with Low Doubling Dimensions", in the SIAM International Conference on Data Mining (SDM'21): 630-638.

    2020

  27. [IJCGA] Yangwei Liu, H. Ding, Ziyun Huang, Jinhui Xu, "Distributed and Robust Support Vector Machine", Int. J. Comput. Geom. Appl. 30(3&4): 213-233 (IJCGA'20)
  28. [TCS]   H. Ding, "Faster balanced clusterings in high dimension", Theor. Comput. Sci. 842: 28-40 (2020).
  29. [JCSS]   H. Ding and J. Xu, "Learning the Truth Vector in High Dimensions", J. Comput. Syst. Sci. 109: 78-94 (2020).
  30. [Algorithmica]   H. Ding and J. Xu, "A Unified Framework for Clustering Constrained Data without Locality Property," Algorithmica 82(4): 808-852 (2020).
  31. [ESA]   H. Ding, "A Sub-linear Time Framework for Geometric Optimization with Outliers in High Dimensions", in the 28th European Symposium on Algorithms (ESA'20).
  32. [IJCAI]   H. Ding, F. Yang and M. Wang, "On Metric DBSCAN with Low Doubling Dimension", in the International Joint Conference on Artificial Intelligence (IJCAI'20).
  33. [ICML]   H. Ding and Z. Wang, "Layered Sampling for Robust Optimization Problems", in International Conference on Machine Learning (ICML'20).

    34. 2019

  34. [Algorithmica]    Z. Huang, H. Ding, and J. Xu, "Faster Algorithm for Truth Discovery via Range Cover", Algorithmica, Volume 81, Issue 10, October, 2019, pp.4118-4133.
  35. [ESA]   H. Ding, H. Yu, and Z. Wang, "Greedy Strategy Works for k-Center Clustering with Outliers and Coreset Construction", The 27th Annual European Symposium on Algorithms (ESA'19), pp.40:1-40:16, Munich/Garching, Germany, September 9-11, 2019.
  36. [AAAI]   H. Ding and M. Ye, "On Geometric Alignment in Low Doubling Dimension", The 33rd AAAI Conference on Artificial Intelligence (AAAI'19), pp.1460-1467, Honolulu, Hawaii, USA, Jan 27-Feb 1, 2019.

    37. 2018

  37. [ESA]   H. Ding and M. Liu, "On Geometric Prototype and Applications", The 26th Annual European Symposium on Algorithms (ESA'18), pp.23:1-23:15, Helsinki, Finland, Aug 20-22, 2018.

    38. 2017

  38. [Algorithmica]    H. Ding and J. Xu, "FPTAS for Minimizing the Earth Mover's Distance Under Rigid Transformations and Related Problems", Algorithmica, Volume 78, Issue 3, July 2017, pp.741-770.
  39. [COCOA]    M. Liu and H. Ding, "Protein Mover's Distance: A Geometric Framework for Solving Global Alignment of PPI Networks", The 11th International Conference on Combinatorial Optimization and Applications (COCOA'17), pp.56-69, Shanghai, China, Dec 16-18, 2017.
  40. [CCCG]    H. Ding, "Balanced k-Center Clustering When k Is A Constant", The 29th Canadian Conference on Computational Geometry (CCCG'17), Ottawa, Canada, July 26-28, 2017.
  41. [WADS]    H. Ding, L. Hu, L. Huang, and J. Li, "Capacitated Center Problems with Two-Sided Bounds and Outliers," The 15th International Algorithms and Data Structures Symposium (WADS'17), pp.325-336, St. John's, Canada, July 31-August 2, 2017.
  42. [WADS]    Z. Huang, H. Ding and J. Xu, "Faster Algorithm for Truth Discovery via Range Cover", The 15th International Algorithms and Data Structures Symposium (WADS'17), pp.461-472, St. John's, Canada, July 31-August 2, 2017.
  43. [AAAI]    Y. Liu, H. Ding, D. Chen, and J. Xu, "Novel Geometric Approach for Global Alignment of PPI Networks," The 31st AAAI Conference on Artificial Intelligence (AAAI'17), pp.31-37, San Francisco, CA, USA, February 4-9, 2017.

    44. 2016

  44. [Chromosoma]    N. Sehgal, B. Seifert, H. Ding, Z. Chen, B. Stojkovic, S. Bhattacharya, J. Xu, and R. Berezney, "Reorganization of the interchromosomal network during keratinocyte differentiation", Chromosoma, Volume 125, Number 3, June 2016, pp.389-403.
  45. [Human Molecular Genetics]    N. Sehgal, A. Fritz, J. Vecerova, H. Ding, Z. Chen, B. Stojkovic, S. Bhattacharya, J. Xu, and R. Berezney, "Large Scale Probabilistic 3-D Organization of Human Chromosome Territories", Human Molecular Genetics, Volume 25, Number 3, February 2016, pp.419-436. (Awarded Cover Page, and recommended by F1000Prime as an Article of Special Significance to its Field)
  46. [JCO]    H. Ding, B. Stojkovic, A. Huges, Z. Chen, L. Xu, A. J. Fritz, R. Berezney, and J. Xu, "Chromatic Kernel and Its Applications", Journal of Combinatorial Optimization, Volume 31, Number 3, April 2016, pp.1298-1315.
  47. [ISAAC]    Y. Liu, H. Ding, Z. Huang, and J. Xu, "Distributed and Robust Support Vector Machine", The 27th International Symposium on Algorithms and Computation (ISAAC'16), 54:1-54:13, Sydney, Australia, December 12-14, 2016.
  48. [ICPR]    Z. Chen, D. Chen, H. Ding, Z. Huang, Z. Li, N. Sehgal, A. Fritz, R. Berezney, and J. Xu, "Finding Rigid Sub-Structure Patterns From 3D Point-Sets", The 23rd International Conference on Pattern Recognition (ICPR'16),Cancun, Mexico, December 4-8, 2016.
  49. [ICML]    H. Ding, Y. Liu, L. Huang, and J. Li, "K-Means Clustering with Distributed Dimensions", The 33rd International Conference on Machine Learning (ICML'16), pp.1339-1348, New York City, NY, USA, June 19-24, 2016.
  50. [MobiHoc]    H. Ding, L. Su, and J. Xu, "Towards Distributed Ensemble Clustering for Networked Sensing Systems: A Novel Geometric Approach", The 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc'16), pp.1-10, Paderborn, Germany, July 4-8, 2016.
  51. [SoCG]    H. Ding, J. Gao, and J. Xu, "Finding Global Optimum for Truth Discovery: Entropy Based Geometric Variance", The 32nd International Symposium on Computational Geometry (SoCG'16), 34:1-34:16, Boston, MA, USA, June 14-18, 2016.

    52. 2015

  52. [Journal of Cellular Physiology]    A. Pliss, A. J. Fritz, B. Stojkovic, H. Ding, L. Mukherjee, S. Bhattacharya, J. Xu, and R. Berezney, "Non-random Patterns in the Distribution of NOR-bearing Chromosome Territories in Human Fibroblasts: A Network Model of Interactions", Journal of Cellular Physiology, Volume 230, Issue 2, February 2015, pp.427-439. (Awarded Cover Page)
  53. [SenSys]    C. Meng, W. Jiang, Y. Li, J. Gao, L. Su, H. Ding, and Y. Cheng, "Truth Discovery on Crowd Sensing of Correlated Entities", The 13th ACM Conference on Embedded Networked Sensor Systems (SenSys'15), pp.169-182, Seoul, South Korea, November 1-4, 2015.
  54. [ACM-BCB]    Z. Chen, H. Ding, D. Chen, X. Wang, A. Fritz, N. Sehgal, R. Berezney, and J. Xu, "Mining k-Median Chromosome Association Graphs from a Population of Heterogeneous Cells", The 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB'15), pp.47-56, Atlanta, GA, USA, September 9-12, 2015.
  55. [AAAI]    H. Ding and J. Xu, "Random Gradient Descent Tree: A Combinatorial Approach for SVM with Outliers," Proc. 29th AAAI Conference on Artificial Intelligence (AAAI'15), pp.2561-2567, Austin, Texas, USA, January 25-30, 2015.
  56. [SODA]    H. Ding and J. Xu, "A Unified Framework for Clustering Constrained Data without Locality Property", Proc. 26th ACM-SIAM Symposium on Discrete Algorithms (SODA'15), pp.1471-1490, San Diego, CA, USA, January 4-6, 2015.

    57. 2014

  57. [PLoS Computational Biology]    A. J. Fritz, B. Stojkovic, H. Ding, J. Xu, S. Bhattacharya, and R. Berezney, "Cell Type Specific Alterations in Interchromosomal Networks Across the Cell Cycle", PLoS Computational Biology, Volume 10, Issue 10, October 2014.
  58. [Human Molecular Genetics]    A.J. Fritz, B. Stojkovic, H. Ding, J. Xu, S. Bhattacharya, D. Galle, and R. Berezney, "Wide-scale Alterations in Interchromosomal Organization in Breast Cancer Cells: Defining a Network of Interacting Chromosomes", Human Molecular Genetics Volume 23, Number 19, October 2014, pp.5133-5146.
  59. [AAAI]    H. Ding and J. Xu, "Finding Median Point-Set Using Earth Mover's Distance", Proc. 28th AAAI Conference on Artificial Intelligence (AAAI'14), pp.1781-1787, Québec City, Québec, Canada, July 27 -31, 2014.
  60. [SoCG]    H. Ding and J. Xu, "Sub-linear Time Hybrid Approximations for Least Trimmed Squares Estimator and Related Problems", Proc. 30th ACM Symposium on Computational Geometry (SoCG'14), pp.110-119, Kyoto, Japan, June 08 - 11, 2014.

    61. 2013

  61. [NIPS]    H. Ding, R. Berezney, and J. Xu, "k-Prototype Learning for 3D Rigid Structures", Advances in Neural Information Processing Systems (NIPS'13), pp.2589-2597, Lake Tahoe, Nevada, USA, December 5-8, 2013.
  62. [ESA]    H. Ding and J. Xu, "FPTAS for Minimizing Earth Mover's Distance under Rigid Transformations", Proc. 21st European Symposium on Algorithms (ESA'13), pp.397-408, Sophia Antipolis, France, September 2-4, 2013.
  63. [CVPR]    H. Ding, B. Stojkovic, R. Berezney, and J. Xu, "Gauging Association Patterns of Chromosome Territories via Chromatic Median", Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR'13), pp.1296-1303, Portland, OR, USA, June 23-28, 2013. Oral presentation (acceptance rate: 3.2%).

    64. 2012

  64. [SPIE Medical Imaging]    L. Xu, B. Stojkovic, H. Ding, Q. Song, X. Wu, M. Sonka, and J. Xu, "Efficient Searching of Globally Optimal and Smooth Multisurfaces with Shape Priors", Proc. SPIE Symposium on Medical Imaging, 83140N, San Diego, California, USA, February 4, 2012.

    65. 2011

  65. [MICCAI Workshop]    L. Xu, B. Stojkovic, H. Ding, Q. Song, X. Wu, M. Sonka, and J. Xu, "Faster Segmentation Algorithm for Optical Coherence Tomography Images with Guaranteed Smoothness", Proc. 2nd International Workshop: Machine Learning in Medical Imaging (Conjunction with MICCAI 2011), pp.308-316, Toronto, Canada, September 18, 2011.
  66. [ICALP]    H. Ding and J. Xu, "Solving the Chromatic Cone Clustering Problem via Minimum Spanning Sphere", Proc. 38th International Colloquium on Automata, Languages and Programming (ICALP'11), pp.773-784, Zurich, Switzerland, July 4-8, 2011.
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