Aarti Singh

A. Nico Habermann Assistant Professor

Machine Learning Department
Carnegie Mellon University


MAIN PUBLICATIONS GROUP TEACHING OUTREACH


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Chronological                                                       By Topics



Graph-structured inference

  • Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic (pdf, arXiv)
    J. Sharpnack, A. Krishnamurthy and A. Singh, Neural Information Processing Systems, NIPS 2013.

  • Recovering Graph-Structured Activations using Adaptive Compressive Measurements (pdf, arXiv)
    A. Krishnamurthy, J. Sharpnack and A. Singh, Asilomar Conference on Signals, Systems, and Computers, 2013, invited paper, Best student paper award.

  • Recovering Block-Structured Activations using Compressive Measurements (arXiv)
    S. Balakrishnan, M. Kolar, A. Rinaldo and A. Singh, Submitted.

  • Detecting Activations over Graphs using Spanning Tree Wavelet Bases (arXiv, pdf)
    J. Sharpnack, A. Krishnamurthy and A. Singh, Artificial Intelligence and Statistics, AISTATS 2013, oral presentation.

  • Changepoint Detection over Graphs with the Spectral Scan Statistic (arXiv, pdf)
    J. Sharpnack, A. Rinaldo and A. Singh, Artificial Intelligence and Statistics, AISTATS 2013.

  • Sparsistency of the Edge Lasso over Graphs (pdf)
    J. Sharpnack, A. Rinaldo, and A. Singh, Artifical Intelligence and Statistics, AISTATS 2012.

  • Identifying graph-structured activation patterns in networks (pdf)
    J. Sharpnack, and A. Singh, Neural Information Processing Systems, NIPS 2010, oral presentation.

  • Detecting weak but hierarchically-structured patterns in networks (pdf, arXiv)
    A. Singh, R. Nowak, and R. Calderbank, Artificial Intelligence and Statistics, AISTATS 2010, oral presentation.

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Clustering

  • Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation (pdf, arXiv)
    M. Azizyan, A. Singh and L. Wasserman, Neural Information Processing Systems, NIPS 2013.

  • Cluster Trees on Manifolds (pdf, arXiv)
    S. Balakrishnan, S. Narayanan, A. Rinaldo, A. Singh and L. Wasserman, Neural Information Processing Systems, NIPS 2013.

  • Efficient Active Algorithms for Hierarchical Clustering (pdf)
    A. Krishnamurthy, S. Balakrishnan, M. Xu and A. Singh, International Conference on Machine Learning, ICML 2012.

  • Stability of Density-Based Clustering (pdf, arXiv)
    A. Rinaldo, A. Singh, R. Nugent, and L. Wasserman, Journal of Machine Learning Research, JMLR, Vol. 13, pages 905-948, 2012.

  • Noise Thresholds for Spectral Clustering (pdf)
    S. Balakrishnan, M. Xu, A. Krishnamurthy, and A. Singh, Neural Information Processing Systems, NIPS 2011, spotlight presentation.

  • Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities (pdf, arXiv)
    B. Eriksson, G. Dasarathy, A. Singh, and R. Nowak, Artificial Intelligence and Statistics, AISTATS 2011.

  • Adaptive Hausdorff Estimation of Density Level Sets (pdf)
    A. Singh, C. Scott and R. Nowak, Annals of Statistics, vol. 37, no. 5B, pp. 2760-2782, 2009.
    Extended version available as Technical Report No. ECE-07-06, ECE Department, University of Wisconsin – Madison.
    A shorter version of this paper appeared in Conference on Learning Theory, COLT 2008, pdf

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Matrix and Subspace inference, Biclustering

  • Low-Rank Matrix and Tensor Completion via Adaptive Sampling (pdf, arXiv)
    A. Krishnamurthy and A. Singh,Neural Information Processing Systems, NIPS 2013.

  • Subspace Detection of High-Dimensional Vectors Using Compressive Sampling (pdf, revision)
    M. Azizyan, and A. Singh, IEEE Statistical Signal Processing Workshop, SSP 2012.

  • Completion of high-rank ultrametric matrices using selective entries (pdf)
    A. Singh, A. Krishnamurhty, S. Balakrishnan and M. Xu, International Conference on Signal Processing and Communications, SPCOM 2012, invited paper.

  • Minimax Localization of Structural Information in Large Noisy Matrices (pdf)
    M. Kolar, S. Balakrishnan, A. Rinaldo, and A. Singh, Neural Information Processing Systems, NIPS 2011, spotlight presentation.

  • Statistical and computational tradeoffs in biclustering (pdf)
    S. Balakrishnan, M. Kolar, A. Rinaldo, A. Singh, and L. Wasserman, NIPS 2011 Workshop on Computational Trade-offs in Statistical Learning.

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Active Learning and Convex Optimization

  • Algorithmic Connections between Active Learning and Stochastic Convex Optimization (pdf)
    A. Ramdas and A. Singh, Algorithmic Learning Theory (ALT), 2013, Accepted.

  • Optimal rates for stochastic convex optimization under Tsybakov noise condition (pdf)
    A. Ramdas and A. Singh, International Conference on Machine Learning (ICML), 2013, oral presentation.
    An older version is available on arXiv.

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Topological inference

  • Tight Lower Bounds for Homology Inference (arXiv)
    S. Balakrishnan, A. Rinaldo, A. Singh and L. Wasserman.

  • Statistical Inference For Persistent Homology (arXiv)
    S. Balakrishnan, B. Fasy, F. Lecci, A. Rinaldo, A. Singh and L. Wasserman, Submitted.

  • Minimax rates for homology inference (arXiv)
    S. Balakrishnan, A. Rinaldo, D. Sheehy, A. Singh, and L. Wasserman, Artifical Intelligence and Statistics, AISTATS 2012, oral presentation.

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Semi-supervised learning

  • Density-sensitive Semisupervised Inference (arXiv)
    M. Azizyan, A. Singh and L. Wasserman, Annals of Statistics, vol. 41, no. 2, pp. 751-771, 2013.

  • Multi-manifold semi-supervised learning (pdf)
    A. Goldberg, X. Zhu, A. Singh, Z. Xu, and R. Nowak, Artificial Intelligence and Statistics, AISTATS 2009.

  • Unlabeled data: Now it helps, now it doesn't (pdf) [Errata]
    A. Singh, R. Nowak and X. Zhu, Neural Information Processing Systems, NIPS 2008, oral presentation.
    Extended version available as Technical Report No. ECE-08-03, ECE Department, University of Wisconsin – Madison.

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Network & Neuroscience Applications

  • Robust Multi-Source Network Tomography Using Selective Probes (pdf, Supplementary file)
    A. Krishnamurthy and A. Singh, IEEE International Conference on Computer Communications, INFOCOM 2012.

  • Controlling the error in fMRI: Hypothesis testing or Set estimation? (pdf)
    Z. Harmany, R. Willett, A. Singh and R. Nowak, IEEE International Symposium on Biomedical Imaging, ISBI 2008.

  • Delay-differentiated Gossiping in Delay Tolerant Networks (pdf)
    P. Ramanathan and A. Singh, IEEE International Conference on Communications, ICC 2008.

  • Active Learning for Adaptive Mobile Sensing Networks (pdf)
    A. Singh, R. Nowak and P. Ramanathan, ACM/IEEE Interntional Conference on Information Processing in Sensor Networks, IPSN 2006.

  • Decentralized Compression and Predistribution via Randomized Gossiping (pdf)
    M. Rabbat, J. Haupt, A. Singh and R. Nowak, ACM/IEEE Interntional Conference on Information Processing in Sensor Networks, IPSN 2006.

  • Spatial Reuse through Adaptive Interference Cancellation in Multi-Antenna Wireless Networks (pdf)
    A. Singh, P. Ramanathan and B. D. Van Veen, IEEE Global Telecommunications Conference, GLOBECOM 2005.

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Microwave Amplification

  • Second- and Third-order Signal Predistortion for Nonlinear Distortion Suppression in a Traveling Wave Tube (pdf)
    A. Singh, J. E. Scharer, J. H. Booske and J. G. Wöhlbier, IEEE Trans. on Electron Devices, Special Issue on Vacuum Electron Devices, pp. 709-717, vol. 52, No. 5, May 2005.

  • Experimental Verification of the Mechanisms for Nonlinear Harmonic Growth and Suppression by Harmonic Injection in a Traveling Wave Tube (pdf)
    A. Singh, J. G. Wöhlbier, J. H. Booske and J. E. Scharer, Physical Review Letters, 92(20), Article 205005, 2004.

  • Sensitivity of Harmonic Injection and its Spatial Evolution for Nonlinear Distortion Suppression in a TWT (pdf)
    A. Singh, J. E. Scharer, J. G. Wöhlbier and J. H. Booske, IEEE International Vacuum Electronics Conference, IVEC 2004.

  • Injection Schemes for TWT Linearization (pdf)
    A. Singh, J. G. Wöhlbier, J. E. Scharer and J. H. Booske, IEEE International Vacuum Electronics Conference, IVEC 2003.

  • Intermodulation Suppression in a Broad Band TWT (pdf)
    A. Singh, J. E. Scharer, M. Wirth, S. Bhattacharjee and J. H. Booske, IEEE International Vacuum Electronics Conference, IVEC 2002.

  • Active Techniques in Chapter 9 "How to Achieve Linear Amplification", Modern Microwave and Millimeter-Wave Power Electronics, John Wiley and IEEE Press, April 2005 (url)
    A. Singh, J. Scharer and J. Booske.

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Miscellaneous

  • Distribution-free Distribution Regression (arXiv, pdf)
    B. Poczos, A. Rinaldo, A. Singh and L. Wasserman, Artificial Intelligence and Statistics, AISTATS 2013, oral presentation.

  • Nonparametric set estimation problems in statistical inference and learning (pdf)
    Ph.D. Thesis, University of Wisconsin - Madison, August 2008.

  • Experimental investigation of TWT nonlinearities and distortion suppression by signal injection (pdf)
    M.S. Thesis, University of Wisconsin - Madison, Dec 2003.

  • Nonlinear behavior and intermodulation suppression in a TWT amplifier (presentation)
    MURI Teleconference presentation, University of Wisconsin - Madison, 2003.

  • Adaptive noise cancellation and its applications (pdf)
    Undergraduate B.E. Project Report, Netaji Subhas Institute of Technology, 2001.

  • Study of MDS matrix used in Twofish AES (Advanced Encryption Standard) Algorithm and its VHDL Implementation (pdf)
    Technical report, Central Electronics Engineering Research Institute, 2000.

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