Jiaji Huang – Publications

Journal Papers

J. Huang, Q. Qiu and R. Calderbank. The Role of Principal Angles in Subspace Classification.
IEEE Transaction on Signal Processing, vol. 64, no. 8, 2016, 1933-1945. [PDF]

L. Wang*, J. Huang*, X. Yuan*, K. Krishnamurthy, J. Greenberg, V. Cevher, M. Rodrigues, D. Brady, R. Calderbank, and L. Carin. Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements. SIAM Journal on Imaging Sciences (SIIMS), vol. 8, no. 3, 1923-1954, 2015. (*: equal contribution) [PDF]

Y. Xie, J. Huang, and R. Willett. Changepoint detection for high-dimensional time series with missing data,
IEEE Journal of Selected Topics on Signal Processing (J-STSP), vol. 7, no. 1, pp. 12-27. 2013. [PDF]

Y. Zhou, Z. Ye, and J. Huang. Improved decision-based detail-preserving variational method for removal of random-valued impulse noise.
IET Image Processing, Vol. 6, no. 7, pp. 976-985, 2012. [PDF]

Conference Papers (Selected)

J. Huang, Q. Qiu and K. W. Church. Exploiting a Zoo of Checkpoints for Unseen Tasks.   [PDF]
Neural Information Processing Systems (Neurips) 2021.

J. Huang, X. Cai and K. W. Church. Improving Bilingual Lexicon Induction for Low Frequency Words.
In proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020.  [PDF] [Talk]

J. Huang, Q. Qiu and K. W. Church. Hubless Nearest Neighbor Search for Bilingual Lexicon Induction.
In Annual Meeting of the Association for Computational Linguistics (ACL), 2019.  [PDF] [Supplementary] [Code]

J. Huang, Y. Li, W. Ping and L. Huang. Large Margin Neural Language Model.
In Empirical Methods in Natural Language Processing (EMNLP), 2018.   [PDF] [Talk]

W. Zhu, Q. Qiu, J. Huang, R. Calderbank, G. Sapiro, and I. Daubechies. LDMNet: Low dimensional manifold regularized neural networks.
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF] [Code]

W. Wang, Z. Gan, W. Wang, D. Shen, J. Huang, W. Ping, S. Satheesh and L. Carin. Topic Compositional Neural Language Model.
Artificial Intelligence and Statistics (AISTATS), 2018. [PDF]

J. Huang, Q. Qiu, R. Calderbank and G. Sapiro, Discriminative Robust Transformation Learning.
Neural Information Processing Systems (NIPS), 2015. [PDF]

J. Huang, Q. Qiu, R. Calderbank and G. Sapiro, Geometry-aware Deep Transform.
International Conference on Computer Vision (ICCV), 2015 [PDF]

L. Wang, J. Huang, X. Yuan, V. Cevher, M. Rodrigues, R. Calderbank, L. Carin. A concentration-of-measure inequality for multiple-measurement models.
IEEE International Symposium on Information Theory (ISIT), 2015.

J. Huang, Q. Qiu, R. Calderbank, M. Rodrigues and G. Sapiro, Alignment with Intra-class Structure can imporve classification.
40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015. [PDF]

J. Huang, X. Yuan and R. Calderbank, Multiscale bayesian reconstruction of compressive X-Ray image.
40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015. [PDF]

J. Huang, X. Yuan and R. Calderbank, Collaborative compressive X-Ray Image reconstruction.
40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015. [PDF]

X. Yuan, J. Huang, Polynomial-phase signal direction-finding and source-tracking with a single accoustic vector sensor.
40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015. [PDF]

J. Huang and X. Ning. Latent Space Tracking from Heterogeneous Data with an Application for Anomaly Detection.
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2015. [PDF]

Workshop Papers

J. Huang, R. Child, V. Rao, H. Liu, S. Satheesh and A. Coates, Active Learning for Speech Recognition: the Power of Gradients.
Workshop of Neural Information Processing Systems on Continual Learning and Deep Networks (NIPS-CLDL), 2016. [PDF]

Y. Xie, J. Huang, and R. Willett. Multiscale online tracking of manifolds,
2012 IEEE Statistical Signal Processing Workshop (SSP). [PDF]

Preprints

J. Huang, Q. Qiu, R. Calderbank and G. Sapiro. GraphConnect: A Regularization Framework for Neural Networks. arXiv preprint arXiv:1512.06757, 2015. [PDF]

Thesis

Learning from Geometry [PDF]