A Physics-Informed Machine Learning Framework for Permafrost Stability Assessment.
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IEEE Access, 2025
Importance Sampling Approach to Chance-Constrained DC Optimal Power Flow.
IEEE Trans. Control. Netw. Syst., June, 2024
Long-term drought prediction using deep neural networks based on geospatial weather data.
Environ. Model. Softw., 2024
A-Priori Reduction of Scenario Approximation for Automated Generation Control in High-Voltage Power Grids With Renewable Energy.
IEEE Control. Syst. Lett., 2024
Cascading Blackout Severity Prediction with Statistically-Augmented Graph Neural Networks.
CoRR, 2024
Climate Change Impact on Agricultural Land Suitability: An Interpretable Machine Learning-Based Eurasia Case Study.
IEEE Access, 2024
From Data to Decisions: Streamlining Geospatial Operations with Multimodal GlobeFlowGPT.
Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, 2024
GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow.
Softw. Impacts, May, 2023
CMIP X-MOS: Improving Climate Models with Extreme Model Output Statistics.
CoRR, 2023
Climate Change Impact on Agricultural Land Suitability: An Interpretable Machine Learning-Based Eurasia Case Study.
CoRR, 2023
GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow.
CoRR, 2023
Long-Term Hail Risk Assessment with Deep Neural Networks.
Proceedings of the Advances in Computational Intelligence, 2023
Efficient numerical methods to solve sparse linear equations with application to PageRank.
Optim. Methods Softw., 2022
Power Grid Reliability Estimation via Adaptive Importance Sampling.
IEEE Control. Syst. Lett., 2022
Long-term hail risk assessment with deep neural networks.
CoRR, 2022
Ranking-Based Physics-Informed Line Failure Detection in Power Grids.
CoRR, 2022
Predicting spatial distribution of Palmer Drought Severity Index.
CoRR, 2022
Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian Processes.
CoRR, 2022
Data-Driven Stochastic AC-OPF using Gaussian Processes.
CoRR, 2022
Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation (Extended Abstract).
CoRR, 2022
Recommender Systems: When Memory Matters.
Proceedings of the Advances in Information Retrieval, 2022
Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation.
J. Artif. Intell. Res., 2021
User preference and embedding learning with implicit feedback for recommender systems.
Data Min. Knowl. Discov., 2021
Learning over no-Preferred and Preferred Sequence of items for Robust Recommendation.
CoRR, 2020
Tractable Minor-free Generalization of Planar Zero-field Ising Models.
CoRR, 2019
A New Family of Tractable Ising Models.
CoRR, 2019
Learning a Generator Model from Terminal Bus Data.
CoRR, 2019
Sequential Learning over Implicit Feedback for Robust Large-Scale Recommender Systems.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
Entropy-Penalized Semidefinite Programming.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Inference and Sampling of $K_33$-free Ising Models.
Proceedings of the 36th International Conference on Machine Learning, 2019
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm.
J. Artif. Intell. Res., 2018
Inference and Sampling of K<sub>33</sub>-free Ising Models.
CoRR, 2018
Gauges, Loops, and Polynomials for Partition Functions of Graphical Models.
CoRR, 2018
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm (Extended Abstract).
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Heterogeneous Dyadic Multi-task Learning with Implicit Feedback.
Proceedings of the Neural Information Processing - 25th International Conference, 2018
Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow.
Proceedings of the 2018 Annual American Control Conference, 2018
Importance sampling the union of rare events with an application to power systems analysis.
CoRR, 2017
Representation Learning and Pairwise Ranking for Implicit and Explicit Feedback in Recommendation Systems.
CoRR, 2017
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Efficient rank minimization to tighten semidefinite programming for unconstrained binary quadratic optimization.
Proceedings of the 55th Annual Allerton Conference on Communication, 2017
Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm.
CoRR, 2016
Tight Risk Bounds for Multi-Class Margin Classifiers.
CoRR, 2015