Publications

  1. Multi-Perspective Abstractive Answer Summarization, Alexander R. Fabbri, Xiaojian Wu, Srini Iyer, Mona Diab, Preprint, 2021.

  2. Unsupervised Energy-based Adversarial Domain Adaptation for Cross-domain Text Classification, Han Zou, Jianfei Yang and Xiaojian Wu, To Apear at Findings of ACL 2021.

  3. Rafael M. Almeida, Qinru Shi, Jonathan M. Gomes-Selman, Xiaojian Wu, Yexiang Xue, Hector Angarita, Nathan Barros, Bruce R. Forsberg, Roosevelt GarcĂ­a-Villacorta, Stephen K. Hamilton, John M. Melack, Mariana Montoya, Guillaume Perez, Suresh A. Sethi, Carla P. Gomes, Alexander S. Flecker. Reducing greenhouse gas emissions of Amazon hydropower with strategic dam planning. Nature Communications, 2019; 10 (1) DOI: 10.1038/s41467-019-12179-5. News: https://www.miragenews.com/ai-helps-shrink-amazon-dams-greenhouse-gas-emissions/ https://www.sciencedaily.com/releases/2019/09/190919134703.htm

  4. Carla Gomes, Thomas Dietterich, Christopher Barrett, Jon Conrad, Bistra Dilkina, Stefano Ermon, Fei Fang, Andrew Farnsworth, Alan Fern, Xiaoli Fern, Daniel Fink, Douglas Fisher, Alexander Flecker, Daniel Freund, Angela Fuller, John Gregoire, John Hopcroft, Steve Kelling, Zico Kolter, Warren Powell, Nicole Sintov, John Selker, Bart Selman, Daniel Sheldon, David Shmoys, Milind Tambe, Weng-Keen Wong, Christopher Wood, Xiaojian Wu, Yexiang Xue, Amulya Yadav, Abdul-Aziz Yakubu, Mary Lou Zeeman. Computational sustainability: Computing for a better world and a sustainable future. Communications of the ACM 62, no. 9 (2019): 56-65. Cover story of CACM!

  5. Efficiently Approximating the Pareto Frontier: Hydropower Dam Placement in the Amazon Basin, Xiaojian Wu, Jonathan Gomes-Selman, Qinru Shi, Yexiang Xue, Roosevelt Garcia-Villacorta, Elizabeth Anderson, Suresh Sethi, Scott Steinchneider, Alexander Flecker, Carla P. Gomes, Proceedings of Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018. [supplementary materials]

  6. Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Networks, Johan Bjorck, Yiwei Bai, Xiaojian Wu, Yexiang Xue, Mark Whitmore, Carla P. Gomes. Proceedings of Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018.

  7. XOR-Sampling for Network Design with Correlated Stochastic Events, X. Wu*, Y. Xue*, B. Selman, C. Gomes, Proceedings of the Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI-17), Melbourne, Australia, 2017. Dataset.

  8. Stochastic Network Design: Models and Scalable Algorithms, X. Wu, Ph.D. thesis, University of Massachusetts Amherst, 2017.

  9. Robust Optimization for Tree-Structured Stochastic Network Design, X. Wu, A. Kumar, D. Sheldon, and S. Zilberstein, Proceedings of the Thirty-First Conference on Artificial Intelligence (AAAI-17), San Francisco, California, 2017. Best Paper Award, Computational Sustainability Track

  10. Dynamic Optimization of Landscape Connectivity Embedding Spatial-Capture-Recapture Information, Y. Xue, X. Wu, D. Morin, B. Dilkina, A. Fuller, J. Royle, and C. Gomes, Proceedings of the Thirty-First Conference on Artificial Intelligence (AAAI-17), San Francisco, California, 2017. [supplementary materials]

  11. Optimizing Resilience in Large Scale Networks, X. Wu, D. Sheldon, and S. Zilberstein, Proceedings of the Thirtieth Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, 2016.

  12. Efficient Algorithms to Optimize Diffusion Processes under the Independent Cascade Model, X. Wu, D. Sheldon, and S. Zilberstein, NIPS Workshop on Networks in the Social and Information Sciences, 2015.

  13. Optimal Threshold Control for Energy Arbitrage with Degradable Battery Storage, M. Petrik, X. Wu, Proceedings of the 31th Conference on Uncertainty in Artificial Intelligence (UAI-15), Amsterdam, Netherlands, 2015.

  14. Approximate Algorithms for Stochastic Network Design, X. Wu, IJCAI Doctoral Consortium 2015

  15. Fast Combinatorial Algorithm for Optimizing the Spread of Cascades, X. Wu, D. Sheldon, and S. Zilberstein, Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI-15), Buenos Aires, Argentina, 2015.

  16. Stochastic Network Design in Bidirected Trees, X. Wu, D. Sheldon, and S. Zilberstein, Proceedings of the Twenty-Eighth Neural Information Processing Systems Conference (NIPS-14), Montreal, Canada, 2014.

  17. Optimizing and Learning Diffusion Behaviors in Complex Network, X. Wu, AAAI Doctoral Consortium 2014

  18. Rounded Dynamic Programming for Tree-Structured Stochastic Network Design, X. Wu, D. Sheldon, and S. Zilberstein, Proceedings of the Twenty-Eighth Conference on Artificial Intelligence (AAAI-14), 479-485, Quebec City, Canada 2014.

  19. Stochastic Network Design for River Networks, X. Wu, D. Sheldon, and S. Zilberstein, NIPS Workshop on Machine Learning for Sustainability, 2013.

  20. Parameter Learning for Latent Network Diffusion, X. Wu, A. Kumar, D. Sheldon, and S. Zilberstein, Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI-13), 2923-2930, Beijing, China, 2013.

  21. Lagrangian Relaxation Techniques for Scalable Spatial Conservation Planning, A. Kumar, X. Wu and S. Zilberstein, Proceedings of the Twenty-Sixth Conference on Artificial Intelligence (AAAI-12), 309-315, Toronto, Canada, 2012.

  22. Influence Diagrams with Memory States: Representation and Algorithms, X. Wu, A. Kumar, and S. Zilberstein. Proceedings of the Second International Conference on Algorithmic Decision Theory (ADT-11), Rutgers University, 2011.

  23. Learning Optimal Bayesian Networks Using A* Search, C. Yuan, B. Malone and X. Wu. 22nd International Joint Conference on Artificial Intelligence (IJCAI-11). Barcelona, Catalonia, Spain, July 2011.

  24. Solving Multistage Influence Diagrams Using Branch-and-Bound Search, C. Yuan, X. Wu, E. Hansen, Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI-10). July 8-11, 2010. Catalina Island, CA.

  25. Solving Influence Diagrams Using Heuristic Search, C. Yuan, X. Wu. Proceedings of the Eleventh International Symposium on Artificial Intelligence and Mathematics (ISAIM-10). January 6-8, 2010. Ft Lauderdale, FL.

  26. A Bayesian Approach for Motivational Diagnosis in Computer-Supported Collaborative Learning Environment, C. Yuan, K. Xie, X. Wu. Proceedings of the International Symposium on Knowledge Acquisition and Modeling (KAM 2008).