Conference Proceedings – Applied Artificial Intelligence Lab

Bashardoust, A., Negin, S., Haki, K., & Shrestha, Y. R. (2023) Employing Machine Learning to Advance Agent-based Modeling in Information Systems Research (ICIS) International Conference on Information Systems
Herath, S., Jóhannsson, J. G., Shrestha, Y. R., & von Krogh, G. F. (2023). Artificial Intelligence-Augmented Decision Making in Supply Chain Monitoring: An Action Design Research Study. Presented at the European Conference on Information Systems (ECIS 2023), Kristiansand, Norway, June 2023. paper

Erdös Number: 4 (Erdös > Noga Alon > Rudolf Fleischer > Jiong Guo > Yash Raj Shrestha)

Pokhrel, S., Bhandari, S., Vasquez, E., Shrestha, YR & Bhattarai, B. (2024). Cross-task Data Augmentation by Pseudo-label Generation for Region-based Coronary Artery Instance Segmentation. MICCAI

Jamet, H., Manderlier, M., Shrestha, Y. R. and Vlachos, M. (2024). Evaluation and simplification of text difficulty using LLMs in the context of recommending texts in French to facilitate language learning. RecSys

Poudel, P., Shrestha, P., Amgain, S., Shrestha, Y. R., Gyawali, P. & Bhattarai B. (2024). CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing Modalities. MICCAI

Bashardoust, A., Feuerriegel, S., & Shrestha, Y. R. (2024). Comparing the willingness to share for human-generated vs. AI-generated fake news. CSCW

Jamet H, Shrestha YR, Vlachos M (2024). Difficulty Estimation and Simplification of French Texts Using LLMs. Intelligent Tutoring Systems (ITS)

Keidar, D., Zhong, M., Zhang, C., Shrestha, Y. R., & Paudel, B. (2021). Towards Automatic Bias Detection in Knowledge Graphs. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: Findings (EMNLP 2021). Nov 7–11, 2021 paper video

Arduini, M., Noci, L., Pirovano, F., Zhang, C., Shrestha, Y. R., & Paudel, B. (2020). Adversarial learning for debiasing knowledge graph embeddings. In MLG 2020: 16th International Workshop on Miningand Learning with Graphs – A Workshop at the KDD Conference, August 24,2020, San Diego, CA.ACM, New York, NY, USA, 7 pages paper video

Leopold F., Shrestha, Y. R. & Paudel, B. (2020). A Deep Learning Pipeline for Patient Diagnosis Prediction Using Electronic Health Records. In BioKDD 2020: 19th International Workshop on Data Mining in Bioinformatics, August 24, 2020, San Diego, CA.ACM, New York, NY, USA paper video

Shrestha, Y. R., & Yang, Y. (2019). Fairness in Algorithmic Decision-Making: Applications in Multi-Winner Voting, Machine Learning, and Recommender Systems. Algorithms, 12(9), 199. paper

Yang, Y., Shrestha, Y. R., & Guo, J. (2016). How Hard Is Bribery with Distance Restrictions? In Proceedings of European Conference on Artificial Intelligence, 363-371 paper

Yang, Y., Shrestha, Y. R., Li, W., & Guo, J. (2016). Kernelization of two path searching problems on split graphs. In Frontiers in Algorithmics , Lecture Notes in Computer Science, 238-249. paper

Mnich, M., Shrestha, Y. R., & Yang, Y. (2015). When does Schwartz conjecture hold? In Proceedings of the International Joint Conference on Artificial Intelligence, 603-609 paper

Guo, J., Shrestha, Y. R., & Yang, Y. (2015). How Credible is the Prediction of a Party-Based Election? In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 1431-1439. International Foundation for Autonomous Agents and Multiagent Systems. paper

Yang, Y., Shrestha, Y. R., & Guo, J. (2015). How Hard is Bribery in Party Based Elections?. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems,1725-1726. International Foundation for Autonomous Agents and Multiagent Systems. paper

Guo, J., Shrestha, Y. R. (2014). Controlling Two-stage Voting Rules, In Proceedings of European Conference on Artificial Intelligence, Frontiers of Artificial Intelligence and Applications, 263, 411-416 paper

Guo, J., & Shrestha, Y. R. (2014) Parameterized Complexity of Edge Interdiction Problems In: Computing and Combinatorics, Lecture Notes in Computer Science, vol. 8591, 166-178 paper

Guo, J., & Shrestha, Y. R. (2014). Complexity of Disjoint Π-Vertex Deletion for Disconnected Forbidden Subgraphs. In Algorithms and Computation, Lecture Notes in Computer Science, vol. 8344, 286-297 paper

Guo, J., & Shrestha, Y. R. (2012). Kernelization and Parameterized Complexity of Star Editing and Union Editing. In Algorithms and Computation, Lecture Notes in Computer Science, vol. 7676, 126-135 paper