- How Good Are My Predictions? Efficiently Approximating Precision-Recall Curves for Massive Datasets, by A. Sabharwal* and H. Sedghi*, accepted for plenary presentation at Uncertainty in Artificial Intelligence (UAI), 2017
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- Knowledge Completion for Generics using Guided Tensor Factorization, by H. Sedghi and A. Sabharwal, accepted for publication in Transactions of the Association for Computational Linguistics (TACL), 2017
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- Training Input-Output Recurrent Neural Networks through Spectral Methods, by H. Sedghi and A. Anandkumar, March 2016
- Provable Tensor Methods for Learning Mixtures of Generalized Linear Models, by H. Sedghi, M. Janzamin and A. Anandkumar, accepted in Artificial Intelligence and Statistics (AISTATS) 2016.
- FEAST at Play: Feature ExtrAction using Score function Tensors, by M. Janzamin*, H. Sedghi*, UN Niranjan*, A. Anandkumar, In NIPS Feature Extraction: Modern Questions and Challenges, Montreal, Canada, December 2015.
- Beating the Perils of Non-Convexity: Guaranteed Training of Neural Networks using Tensor Methods, by M. Janzamin, H. Sedghi and A. Anandkumar, June. 2015.
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- Learning Mixed Membership Community Models in Social Tagging Networks through Tensor Methods, by A. Anandkumar and H. Sedghi, April 2015.
- Score Function Features for Discriminative Learning: Matrix and Tensor Framework, by M. Janzamin, H. Sedghi and A. Anandkumar, Dec. 2014.
Provable Methods for Training Neural Networks with Sparse Connectivity
, by H. Sedghi and A. Anandkumar, accepted for presentation in Neural Information Processing Systems (NIPS) Deep Learning Workshop, Montreal, 2014.
and in International Conference on Learning Representation (ICLR), May, 2015.
- Multi-Step Stochastic ADMM in High Dimensions: Applications in Sparse Optimization and Noisy Matrix Decomposition, by H. Sedghi, A. Anandkumar, E. Jonckheere. Neural Information Processing Systems (NIPS), Montreal, 2014.
Download: NIPS version,PDF, video.
- Statistical Structure Learning to Ensure Data Integrity in Smart Grid, by H. Sedghi and E. Jonckheere. Accepted for publication in IEEE Transactions on Smart Grid.
- Statistical Structure Learning of Smart Grid for Detection of False Data Injection, H. Sedghi and E. Jonckheere, IEEE Power and Energy Society General Meeting2013.
- On Conditional Mutual Information in Gaussian-Markov Structured Grids, H. Sedghi and E. Jonckheere, Information and Control in Networks, G. Como, B. Bernhardson, and A. Rantzer, vol. 450, pp 277-297, Springer.
- A Misbehavior-Tolerant Multipath Routing Protocol for Wireless Ad hoc Network, H. Sedghi, M.R. Pakravan and M. R. Aref, International Journal of Research in Wireless Systems, vol. 2, issue 2.
- A Game-Theoretic Approach for Power Allocation in Bidirectional Cooperative Communication, M.Janzamin, M. R. Pakravan and H. Sedghi, IEEE Wireless Communication and Networking Conference (WCNC) Sydney, 2010.