LIST OF PUBLICATIONS/BOOKS (reverse chronological order)
Books:
1. Vinod Kumar Chauhan (2021), "Stochastic Optimization for Large-scale Machine Learning", CRC Press, ISBN 9781032131757, book
Preprints/Under Review Papers:
6. Vinod Kumar Chauhan, L. Clifton, A. Salaun, Y. Lu, K. Branson, P. Schwab, G. Nigam and D. A. Clifton, “Sample Selection Bias in Machine Learning for Healthcare”, (under review), 2024, arXiv: 2405.07841, preprint.
5. Sukhdeep Singh, Anuj Sharma, Vinod Kumar Chauhan (2024) GTAGCN: Generalized Topology Adaptive Graph Convolutional Networks, arXiv:2403.15077, preprint.
4. Vinod Kumar Chauhan, Jiandong Zhou, Ping Lu, Soheila Molaei, David A. Clifton (2023) A Brief Review of Hypernetworks in Deep Learning, arXiv:2306.06955, preprint (under review).
3. Taha Ceritli, Ghadeer O. Ghosheh, Vinod Kumar Chauhan, Tingting Zhu, Andrew P. Creagh, David A. Clifton (2023) Synthesizing Mixed-type Electronic Health Records using Diffusion Models, arXiv:2302.14679, preprint (under review).
2. Lee, Brandon; Alomari, Muhannad; Vinod Kumar Chauhan; Farsi, Maryam; Brintrup, Alexandra "Predicting supply chain procurement bid prices with uncertainty quantification and machine learning: a case study in aerospace manufacturing", (under review @Annals of OR).
1. Vinod Kumar Chauhan, Mark Bass, Ajith Kumar Parlikad, Alexandra Brintrup (2022) "Trolley optimisation: An extension of bin packing to load PCB components", arXiv:2209.09116, preprint (under review)
Published Papers:
28. Vinod Kumar Chauhan, Jiandong Zhou, Ghadeer Ghosheh, Soheila Molaei, David A. Clifton (2024) Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation. The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), May 2-4, 2024, Valencia, Spain, paper, poster, preprint, code.
27. Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue, Omid Rohanian, Soheila Molaei, and David A. Clifton (2024) Continuous Patient State Attention Model for Addressing Irregularity in Electronic Health Records, BMC Medical Informatics and Decision Making, paper, preprint, code.
26. Vinod Kumar Chauhan, Sukhdeep Singh, Anuj Sharma. HCR-Net: A deep learning based script independent handwritten character recognition network, Multimedia Tools and Applications, preprint, paper, code.
25. Oscar Hou In Chou*, Vinod Kumar Chauhan*, Cheuk To Chung, Lei Lu, Teddy Tai Loy Lee, Zita Man Wai Ng, Karin Kai Wang, Sharen Lee, Haipeng Liu, Wing Tak Wong, Ronald Ting Kai Pang, Apichat Kaewdech, Bernard M.Y. Cheung, Gary Tse, Jiandong Zhou (2024) Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study. Gastric Cancer, paper, preprint (free).
24. S. Molaei, N. G. Bousejin, G. Ghosheh, A. Thakur, Vinod Kumar Chauhan, T. Zhu, D. Clifton (2024) CliqueFluxNet: Unveiling EHR Insights with Stochastic Edge Fluxing and Maximal Clique Utilisation using Graph Neural Networks. Journal of Healthcare Informatics Research, (in press), preprint.
23. S. Molaei, G. Niknam, G. Ghosheh, Vinod Kumar Chauhan, H. Zare, T. Zhu, S. Pan, D. Clifton (2024) Temporal Dynamics Unleashed: Elevating Variational Graph Attention. Knowledge-Based Systems, paper.
22. Oscar Hou In Chou, Vinod Kumar Chauhan, Cheuk To Chung, Lei Lu, Teddy Tai Loy Lee, Zita Man Wai Ng, Karin Kai Wang, Sharen Lee, Haipeng Liu, Wing Tak Wong, Ronald Ting Kai Pang, Apichat Kaewdech, Bernard M.Y. Cheung, Gary Tse, Jiandong Zhou (2023). 1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study. Annals of Oncology, 34, S876. abstract
21. Vinod Kumar Chauhan, Soheila Molaei, Marzia Hoque Tania, Anshul Thakur, Tingting Zhu and David Clifton (2023) Adversarial De-confounding in Individualised Treatment Effects Estimation, The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:837-849, 2023, paper, poster, preprint, code, video.
20. Omid Rohanian, Hannah Jauncey, Mohammadmahdi Nouriborji, Vinod Kumar Chauhan, Bronner P. Gonçalves, Christiana Kartsonaki, ISARIC Clinical Characterisation Group, Laura Merson, David Clifton (2023) Using Bottleneck Adapters to Identify Cancer in Clinical Notes under Low-Resource Constraints, The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, preprint, paper
19. Sukhdeep Singh, Anuj Sharma, Vinod Kumar Chauhan (2023) Indic Script Family and Its Offline Handwriting Recognition for Characters/ Digits and Words: A Comprehensive Survey, Artificial Intelligence Review paper.
18. Atieh Khodadadi, Nima Ghanbari Bousejin, Soheila Molaei*, Vinod Kumar Chauhan, Tingting Zhu, David Clifton (2023) Improving Diagnostics with Deep Forest Applied to Electronic Health Records, Sensors, paper.
17. Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue and David A. Clifton (2022) COPER: Continuous Patient State Perceiver, IEEE International Conference on Biomedical and Health Informatics (IEEE BHI-2022) paper
16. Vinod Kumar Chauhan, Anna Ledwoch, Alexandra Brintrup, Manuel Herrera, Vaggelis Giannikas, Goran Stojkovic, Duncan Mcfarlane (2023) "Network science approach for identifying disruptive elements of an airline", Data Science and Management, Elsevier, preprint, paper.
15. Vinod Kumar Chauhan, Muhannad Alomari, James Arney, Ajith Kumar Parlikad, Alexandra Brintrup (2023). "Exploitation of material consolidation trade-offs in multi-tier complex supply networks", Supply Chain Analytics, paper, preprint, code
14. Vinod Kumar Chauhan, Stephen Mak, Ajith Kumar Parlikad, Muhannad Alomari, Linus Casassa and Alexandra Brintrup (2022) "Real-time large-scale supplier order assignments across two-tiers of a supply chain with penalty and dual-sourcing", Computers & Industrial Engineering, DOI: 10.1016/j.cie.2022.108928, paper, preprint
13. Vaggelis Giannikasa, Anna Ledwoch, Goran Stojkovic, Pablo Costas, Alexandra Brintrup, Ahmed Ali Saeed Al-Ali, Vinod Kumar Chauhan, Duncan McFarlane (2022) A data-driven method to assess the causes and impact of delay propagation in air transportation systems, Transportation Research Part C: Emerging Technologies, paper.
12. Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya (2021) LIBS2ML: A Library for Scalable Second Order Machine Learning Algorithms. Software Impacts, Elsevier, DOI: 10.1016/j.simpa.2021.100123, paper, preprint, blog, code.
11. Sukhdeep Singh, Anuj Sharma, Vinod Kumar Chauhan (2021) Online handwritten Gurmukhi word recognition using fine-tuned Deep Convolutional Neural Network on offline features. Machine Learning with Applications, Elsevier, DOI: 10.1016/j.mlwa.2021.100037, paper.
10. Vinod Kumar Chauhan, Supun Perera, Alexandra Brintrup (2020) The relationship between nested patterns and the ripple effect in complex supply networks. International Journal of Production Research, 59:1, 325-341, DOI: 10.1080/00207543.2020.1831096 paper
9. Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya (2020) Stochastic Trust Region Inexact Newton Method for Large-scale Machine Learning. Journal of Machine Learning and Cybernetics 11, 1541-1555, DOI:10.1007/s13042-019-01055-9 paper, preprint, code
8. Sukhdeep Singh, Vinod Kumar Chauhan, Elisa H. Barney Smith (2020) A Self Controlled RDP Approach for Feature Extraction in Online Handwriting Recognition using Deep Learning, Applied Intelligence, 50, 2093–2104, DOI:10.1007/s10489-020-01632-4 paper.
7. Vinod Kumar Chauhan (2019) Solving large scale linear support vector classification using an optimization framework based on stochastic approximation and coordinate descent approaches, Panjab University Chandigarh, PhD Thesis, link
6. Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya (2019) SAAGs: Biased Stochastic Variance Reduction Methods for Large-scale Learning. Applied Intelligence, Springer, Volume 49, Issue 9, pp 3331–3361, DOI: 10.1007/s10489-019-01450-3 paper preprint BibTex
5. Vinod Kumar Chauhan, Kalpana Dahiya, Anuj Sharma (2019) Problem Formulations and Solvers in Linear SVM: a Review. Artificial Intelligence Review, Springer, Volume 52, Issue 2, pp 803–855, DOI: 10.1007/s10462-018-9614-6, paper BibTex
4. Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya (2018) Faster Learning by Reduction of Data Access Time. Applied Intelligence, Springer 48(12):4715--4729. DOI: 10.1007/s10489-018-1235-x paper arXiv preprint BibTex
Previous preprints (v1 & v2) appeared with a different name, as given below:
Vinod Kumar Chauhan, Kalpana Dahiya, Anuj Sharma (2018) Faster Algorithms for Large-scale Machine Learning using Simple Sampling Techniques. Technical Report, arXiv:1801.05931, preprint BibTex
3. Vinod Kumar Chauhan, Kalpana Dahiya, Anuj Sharma (2017) Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems. Ninth Asian Conference on Machine Learning (ACML), in Proceedings of Machine Learning Research (PMLR) 77:49-64. (acceptance rate - 23.8%; Student Travel Grant Award - ACML Steering Committee) paper BibTex
2. Vinod Kumar Chauhan, Kalpana Dahiya, Anuj Sharma (2017) Trust Region Levenberg-Marquardt Method for Linear SVM. IEEE Proceedings of the 9th International Conference on Advances in Pattern Recognition (ICAPR-2017) DOI: 10.1109/ICAPR.2017.8593090 paper BibTex
1. Kalpana Dahiya, Vinod Kumar Chauhan, Anuj Sharma (2016) Online Support Vector Machine Based on Minimum Euclidean Distance. In: Raman B., Kumar S., Roy P., Sen D. (eds) Proceedings of International Conference on Computer Vision and Image Processing (CVIP-2016). Advances in Intelligent Systems and Computing, vol 459 pp. 89-99 DOI: 10.1007/978-981-10-2104-6_9, Springer, Singapore. paper BibTex
Note: Send me an email to get any of the published papers.
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Talks in Symposia / Conferences:
19. Keynote Speaker, “Prediction of Post-operative Atrial Fibrillation in Patients undergoing Heart Surgery”, Artificial Intelligence (AI) and Digital Transformation in Various Academic Disciplines & Teacher Training, 15th Feb 2024, Government College RaipurRani.
18. Keynote Speaker, “HyperNetworks: A new Approach for Training and Designing Neural Networks”, International Conference on Artificial Intelligence and Machine Learning, Department of Computer Science and Applications, Panjab University, Chandigarh, November 28-29, 2023.
17. Invited talk, "Dynamic Inter-Treatment Information Sharing for Individualised Treatment Effects Estimation", IISER Pune, October 04, 2023, link
16. “Machine Learning in Clinical Decision-Making”, University of Oxford, Critical Care Research Group: Public, Patient Involvement and Engagement Event, September 26, 2023 (20 minutes talk).
15. "Adversarial De-confounding in Individualised Treatment Effects Estimation" in The 26th International Conference on Artificial Intelligence and Statistics (AISTATS-2023), April 25-27, Spain (virtual presentation), video.
14. "COPER: Continuous Patient State Perceiver", in IEEE International Conference on Biomedical and Health Informatics (IEEE BHI-2022), Sept. 27-30, 2022, virtual presentation.
13. "AI: From Everyday Life to Mathematical Foundations", in Online Faculty Development Programme, "Artificial Intelligence and Machine Learning - Basics and Applications", at Panjab University Chandigarh, India on 24 December 2020 (One session of 90 minutes).
12. "Supplier selection and order allocation across two-tiers of a large-scale supply chain with dual-sourcing" DIAL Seminar, IfM, Oct 16, 2020.
11. "Why is Your Flight Late? Mining Airline Data to Access Root-causes and Impact of Delay Propagation" in COW Optimization Workshop (Boeing's Internal Conference) at Gothenburg, Sweden on September 24, 2019.
10. "Solving Large-Scale Machine Learning Problems" Seminar at IfM, University of Cambridge, UK, June 27, 2019.
9. "Solving Large-Scale Machine Learning Problems" in the Faculty Development Program "Recent Trends in Machine Learning" at Gurunanak Dev Engineering College, Ludhiana, March 07, 2018.
8. "Faster Large-Scale Learning Algorithms by Reduction of Data Access Time”, 12th Chandigarh Science Congress (CHASCON-2018) at Panjab University Chandigarh, Feb. 12-14, 2018.
7. "Trust Region Levenberg-Marquardt Method for Linear SVM", the 9th International Conference on Advances in Pattern Recognition (ICAPR-2017), In celebration of the 125th Birth Anniversary of Professor P. C. Mahalanobis, December 27-30, 2017 at Indian Statistical Institute, Bangalore.
6. "Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems", the 9th Asian Conference on Machine Learning, November 15-17, 2017 (ACML 2017), at Yonsei University, Seoul, Korea (acceptance rate - 23.8%; Student Travel Grant Award - ACML Steering Committee).
5. "Batch Block Optimization Framework to Solve Big Data Problems in Machine Learning”, International Symposium on Computational Mathematics, Optimization, and Computational Intelligence (CMOCI-2017), July 17 - 19, 2017 at Indian Institute of Technology Indore, INDIA in collaboration with Nanyang Technological University.
4. "Reduced Sub-problem Approach to solve Big Data Problems”, 11th Chandigarh Science Congress (CHASCON-2017) at Panjab University Chandigarh, March 09-11, 2017.
3. "Trust Region Levenberg Marquardt Method for Linear Support Vector Machines”, 2017 Symposium on Mathematical Programming and Game Theory (SMPGT-2017) at Indian Statistical Institute Delhi, INDIA, January 09-11, 2017.
2. "LMTR Algorithm for Classification”, 10th Chandigarh Science Congress (CHASCON-2016) at Panjab University Chandigarh, 29 Feb-02 March, 2016.
1. "Online Support Vector Machine Based on Minimum Euclidean Distance”, International Conference on Computer Vision and Image Processing (CVIP-2016) at Indian Institute of Technology Roorkee, INDIA, 26-28 February, 2016. (IAPR Sponsored).
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