Publications

  • Unifying task specification in reinforcement learning. Martha White. International Conference on Machine Learning (ICML), 2017. [pdf]

  • Adapting kernel representations online using submodular maximization. Yangchen Pan, Matthew Schlegel and Martha White. International Conference on Machine Learning (ICML), 2017. [pdf]

  • Learning sparse representations in reinforcement learning with sparse coding. Lei Le, Raksha Kumaraswamy and Martha White. International Joint Conference on Artificial Intelligence (IJCAI), 2017. [pdf]

  • Accelerated Gradient Temporal Difference Learning. Yangchen Pan, Adam White and Martha White. AAAI, 2017. [pdf]

  • Recovering true classifier performance in positive-unlabeled learning. Shantanu Jain, Martha White and Predrag Radivojac.
    AAAI, 2017.

  • Estimating the class prior and posterior from noisy positives and unlabeled data . Shantanu Jain, Martha White and Predrag Radivojac. NIPS, 2016. [pdf] 

  • Global optimization of factor models using alternating minimization. Lei Le and Martha White. In submission to JMLR, 2016. [pdf] 

  • Nonparametric semi-supervised learning of class proportions. Shantanu Jain, Martha White, Michael W. Trosset and Predrag Radivojac. In submission to JMLR, 2016. [pdf] 

  • Incremental Truncated LSTD. Clement Gehring, Yangchen Pan and Martha White. International Joint Conference on Artificial Intelligence (IJCAI), 2016. [pdf]

  • Investigating practical, linear temporal difference learning. Adam White and Martha White. Autonomous Agents and Multi-agent Systems (AAMAS), 2016. [pdf]

  • A Greedy Approach to Adapting the Trace Parameter for Temporal Difference Learning . Adam White and Martha White. Autonomous Agents and Multi-agent Systems (AAMAS), 2016. [pdf] 

  • Scalable Metric Learning for Co-embedding. Farzaneh Mirzazadeh, Martha White, Andras Gyorgy and Dale Schuurmans. ECML PKDD, 2015. [pdf]

  • An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning. Richard S. Sutton, A Rupam Mahmood and Martha White. JMLR, 2016. [pdf] 

  • Optimal Estimation of Multivariate ARMA Models. Martha White, Junfeng Wen, Michael Bowling and Dale Schuurmans. Proceedings of the 29th AAAI Conference on Artificial Intelligence, 2015. [pdf] 

  • Partition Tree Weighting. Joel Veness, Martha White, Michael Bowling and Andras Gyorgy. Proceedings of the 2013 Data Compression Conference, 2013. [pdf] 

  • Convex Multi-view Subspace Learning. Martha White, Yaoliang Yu, Xinhua Zhang, and Dale Schuurmans. Advances in Neural Information Processing Systems (NIPS), 2012. [pdf] 

  • Off-Policy Actor-Critic. Thomas Degris, Martha White, Richard S. Sutton. In Proceedings of the Twenty-Ninth International Conference on Machine Learning (ICML), 2012. [pdf] 

  • Generalized Optimal Reverse Prediction. Martha White and Dale Schuurmans. In Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS), 2012. [pdf] 

  • Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions. Xinhua Zhang, Yaoliang Yu, Martha White, Ruitong Huang and Dale Schuurmans. In Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI), 2011. [pdf] 

  • Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains. Martha White and Adam White. In Advances in Neural Information Processing Systems (NIPS), 2010. [pdf] 

  • Relaxed Clipping: A Global Training Method for Robust Regression and Classification. Yaoliang Yu, Min Yang, Linli Xu, Martha White, Dale Schuurmans. In Advances in Neural Information Processing Systems (NIPS), 2010. [pdf] 

  • Learning a Value Analysis Tool For Agent Evaluation. Martha White and Michael Bowling. In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI), 2009. [pdf] 

  • Optimal Reverse Prediction: A Unified Perspective on Supervised, Unsupervised and Semi-supervised Learning. Linli Xu, Martha White, and Dale Schuurmans. In Proceedings of the 26th International Conference on Machine Learning (ICML), 2009. [pdf] 

Theses

  • Martha White. Regularized factor models. PhD thesis,
    Details     BibTeX     Download: [pdf] 
  • Martha White. A General Framework for Reducing Variance in Agent Evaluation. Master's thesis,
    Details     BibTeX     Download: [pdf]