publications by categories in reversed chronological order. An up-to-date list is available on Google Scholar.

  1. ACCV Unified Learning of Multipurpose Energy Based Generative Hashing Network
    Doan, Khoa D, and Reddy, Chandan K
    In Sixteenth Asian Conference on Computer Vision 2022
  2. NeurIPS Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class
    Doan, Khoa D, Lao, Yingjie, and Li, Ping
    In Thirty-Sixth Conference on Neural Information Processing Systems 2022
  3. CVPR One Loss for Quantization: Deep Hashing with Discrete Wasserstein Distributional Matching
    Doan, Khoa D, Yang, Peng, and Li, Ping
    In Conference on Computer Vision and Pattern Recognition 2022
  1. NeurIPS Backdoor Attack with Imperceptible Input and Latent Modification
    Doan, Khoa D, Lao, Yingjie, and Li, Ping
    In Thirty-Fifth Conference on Neural Information Processing Systems 2021
  2. ICCV LIRA: Learnable, Imperceptible and Robust Backdoor Attacks
    Doan, Khoa D, Lao, Yingjie, Zhao, Weijie, and Li, Ping
    In International Conference on Computer Vision 2021
  3. SIGIR Interpretable Graph Similarity Computation via Differentiable Optimal Alignment of Node Embeddings
    Doan, Khoa D, Manchanda, Saurav, Mahapatra, Suchismit, and Reddy, Chandan K
    In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval 2021
  1. WWW Efficient Implicit Unsupervised Text Hashing Using Adversarial Autoencoder
    Doan, Khoa D, and Reddy, Chandan K
    In Proceedings of The Web Conference 2020
  2. arXiv Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space
    arXiv preprint arXiv:2003.11774 2020
  3. arXiv Image Hashing by Minimizing Discrete Component-wise Wasserstein Distance
    arXiv preprint arXiv:2003.00134 2020
  4. arXiv Regression via implicit models and optimal transport cost minimization
    Manchanda, Saurav, Doan, Khoa D, Yadav, Pranjul, and Selvaraj, Sathiya K
    arXiv preprint arXiv:2003.01296 2020
  5. arXiv Gradient boosting neural networks: Grownet
    arXiv preprint arXiv:2002.07971 2020
  1. BigData Targeted display advertising: the case of preferential attachment
    Manchanda, Saurav, Yadav, Pranjul, Doan, Khoa D, and Selvaraj, Sathiya K
    In Proceedings of the 2019 IEEE International Conference on Big Data 2019
  2. CIKM Adversarial Factorization Autoencoder for Look-Alike Modeling
    Doan, Khoa D, Yadav, Pranjul, and Reddy, Chandan K
    In Proceedings of the 28th ACM International Conference on Information and Knowledge Management 2019
  3. PAKDD An Attentive Spatio-Temporal Neural Model for Successive Point of Interest Recommendation.
    Doan, Khoa D, Yang, Guolei, and Reddy, Chandan K
    In Proceedings of the 2019 Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2019
  1. BigData Quest for Value in Big Earth Data
    Kuo, Kwo-Sen, Oloso, Amidu O, Rilee, Mike L, Doan, Khoa D, Clune, Thomas L, and Yu, Hongfeng
    In EGU General Assembly Conference Abstracts 2017
  1. BigData Evaluating the impact of data placement to spark and SciDB with an Earth Science use case
    Doan, Khoa D, Oloso, Amidu O, Kuo, Kwo-Sen, Clune, Thomas L, Yu, Hongfeng, Nelson, Brian, and Zhang, Jian
    In Proceedings of the 2016 IEEE International Conference on Big Data 2016
  2. IGARSS Implications of data placement strategy to Big Data technologies based on shared-nothing architecture for geosciences
    Kuo, Kwo-Sen, Oloso, Amidu, Doan, Khoa D, Clune, Thomas L, and Yu, Hongfeng
    In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2016
  1. AGU SciDB versus Spark: A preliminary comparison based on an Earth science use case
    Clune, Thomas, Kuo, Kwo-Sen, Doan, Khoa D, and Oloso, Amidu
    In AGU Fall Meeting Abstracts 2015
  1. BigData Performance comparison of big-data technologies in locating intersections in satellite ground tracks
    Doan, Khoa D, Oloso, Amidu, Kuo, Kwo-Sen, Clune, Thomas L, and Bayesics, LLC
    In Proceedings of the 2014 ASE BigData/SocialInformatics/PASSAT/BioMedCom Conference 2014
  1. AGU A Demonstration of Big Data Technology for Data Intensive Earth Science
    Kuo, K, Clune, T, Ramachandran, R, Rushing, J, Fekete, G, Lin, A, Doan, KD, Oloso, AO, and Duffy, D
    In AGU Fall Meeting Abstracts 2013
The brick walls are there for a reason. The brick walls are not there to keep us out. The brick walls are there to give us a chance to show how badly we want something -- Randy Pausch