Publications
2024
- [ACM MM] Q. Chen, W. Liu, H. Ding (corresponding author),"A Novel Confidence Guided Training Method for Conditional GANs with Auxiliary Classifier," to appear in ACM Multimedia (ACM MM'24).
- [COCOON] J. Huang, W. Liu, H. Ding, “Bi-criteria Sublinear Time Algorithms for Clustering with Outliers in High Dimensions,” to appear in International Computing and Combinatorics Conference (COCOON 2024).
- [ICML] W. Lin*, J. Chen*, R. Huang, H. Ding, “An Effective Dynamic Gradient Calibration Method for Continual Learning,” to appear in International Conference on Machine Learning (ICML'24) (the first two authors are both first authors).
- [IJCAI] Q. Yang, H. Ding, “Approximate Algorithms For k-Sparse Wasserstein Barycenter With Outliers,” to appear in the International Joint Conference on Artificial Intelligence (IJCAI'24).
- [SIGMOD] G. Mo, S. Song, H. Ding, “Towards Metric DBSCAN: Exact, Approximate, and Streaming Algorithms,” to appear in The 2024 ACM SIGMOD International Conference on Management of Data (SIGMOD'24).
- [DAC] L. Chen, Q. Xu, H. Ding, “OTPlace-Vias: A Novel Optimal Transport Based Method for High Density Vias Placement in 3D Circuits,” to appear in The 61st Design Automation Conference (DAC'24).
- [AAAI] X. Xu, H. Ding, “A Novel Skip Orthogonal List for Dynamic Optimal Transport Problem,” to appear in The 38rd AAAI Conference on Artificial Intelligence (AAAI'24).
2023
- [ICCAD] L. Yang, G. Sun, H. Ding, “Towards Timing-Driven Routing: An Efficient Learning Based Geometric Approach,” 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD). IEEE, 2023: 1-9.
- [MICCAI] W. Liu, H. Ding, “Solving Low-Dose CT Reconstruction via GAN with Local Coherence,” International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer Nature Switzerland, 2023: 524-534.
- [JEA] H. Ding, W. Liu, M. Ye, "A Data-dependent Approach for High-dimensional (Robust) Wasserstein Alignment." ACM Journal of Experimental Algorithmics 28 (2023): 1-32.
2022
- [NeurIPS] R. Huang, J. Huang, W. Liu, H.
Ding (corresponding author), “Coresets for Wasserstein Distributionally
Robust Optimization Problems,” to appear in NeurIPS 2022 (spotlight, acceptance rate<=3%).
- [NeurIPS] J. Chen, Q. Yang, R. Huang, H.
Ding (corresponding author), “Coresets for Relational Data and The
Applications,” to appear in NeurIPS 2022 (spotlight,
acceptance rate<=3%).
- [UAI] Q. Chen*, K. Liu*, R. Yao, H.
Ding (corresponding author), “Sublinear Time Algorithms for Greedy Selection
in High Dimensions,” to appear in 387th Conference on Uncertainty in Artificial
Intelligence (UAI'22) (the first two authors are both first authors).
- [IJCGA] J. Huang, R. Qin, F. Yang, H.
Ding,
“Random Projection and Recovery for High Dimensional Optimization with Arbitrary
Outliers,” to appear in Int. J. Comput. Geom. Appl. (IJCGA).
2021
- [NeurIPS] Z. Wang, Y. Guo, H. Ding
(corresponding author), "Robust and Fully-Dynamic Coreset for Continuous-and-Bounded
Learning (With Outliers) Problems," NeurIPS 2021: 14319-14331 (spotlight, acceptance rate<=3%).
- [NeurIPS] R. Qin, M. Li, H. Ding
(corresponding author), "Solving Soft Clustering Ensemble via k-Sparse Discrete
Wasserstein Barycenter," NeurIPS 2021: 900-913.
- [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.
- [ICML]   J. Huang*, R. Huang*, W. Liu*,
N. Freris, H. Ding (corresponding author), "A Novel Sequential Coreset Method
for Gradient Descent Algorithms, " to appear in International Conference on Machine
Learning (ICML'21): 4412-4422.
(the first three authors are all first authors)
- [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).
- [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
- [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)
- [TCS]   H. Ding, "Faster balanced
clusterings in high dimension," Theor. Comput. Sci. 842: 28-40 (2020).
- [JCSS]   H. Ding and J. Xu,
"Learning the Truth Vector in High Dimensions," J. Comput. Syst. Sci. 109: 78-94
(2020).
- [Algorithmica]   H. Ding and J.
Xu, "A Unified Framework for Clustering Constrained Data without Locality Property,"
Algorithmica 82(4): 808-852 (2020).
- [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).
- [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).
- [ICML]   H. Ding and Z. Wang,
"Layered Sampling for Robust Optimization Problems," in International Conference on
Machine Learning (ICML'20).
2019
- [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.
- [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.
- [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.
2018
- [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.
2017
- [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.
- [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.
- [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.
- [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.
- [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.
- [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.
2016
- [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.
- [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)
- [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.
- [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.
- [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.
- [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.
- [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.
- [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.
2015
- [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)
- [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.
- [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.
- [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.
- [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.
2014
- [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.
- [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.
- [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.
- [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.
2013
- [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.
- [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.
- [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%).
2012
- [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.
2011
- [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.
- [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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