Publications

High-dimensional statistics

  • S. Oymak, and M. Soltanolkotabi, ``Fast and Reliable Parameter Estimation from Nonlinear Observations,'' manuscript Oct. 2016.
  • S. Oymak, B. Recht, and M. Soltanolkotabi, ``Sharp Time-Data Tradeoffs for Linear Inverse Problems,'' under revision Nov 2016.
  • C. Thrampoulidis, S. Oymak, and B. Hassibi. "Recovering Structured Signals in Noise: Least-Squares Meets Compressed Sensing." book chapter in ``Compressed Sensing and its Applications'' 2014.
  • C. Thrampoulidis, S. Oymak, and B. Hassibi, ``Regularized Linear Regression: A Precise Analysis of the Estimation Error,'' COLT 2015.
  • C. Thrampoulidis, S. Oymak, and B. Hassibi, ``Simple Error Bounds for Regularized Noisy Linear Inverse Problems,'' ISIT 2014, arXiv:1401.6578.
  • S. Oymak, C. Thrampoulidis, and B. Hassibi, ``Simple Bounds for Noisy Linear Inverse Problems with Exact Side Information,'' technical report, arXiv:1312.0641.
  • S. Oymak, C. Thrampoulidis, and B. Hassibi, ``The Squared-Error of Generalized LASSO: A Precise Analysis,'' in submission, short version appeared at Allerton 2013, arXiv:1311.0830, code.
  • S. Oymak, A. Jalali, M. Fazel, and B. Hassibi, ``Noisy estimation of simultaneously structured models: Limitations of convex relaxation,'' appeared in CDC 2013.
  • S. Oymak, A. Jalali, M. Fazel, Y. C. Eldar, and B. Hassibi, ``Simultaneously Structured Models with Application to Sparse and Low-rank Matrices,'' Trans. on Info. Theory, arXiv:1212.3753.
  • S. Oymak and B. Hassibi, ``Sharp MSE Bounds for Proximal Denoising,'' Foundations of Computational Mathematics Oct 2015, partial results appeared in Allerton 2012, arXiv:1305.2714.
  • S. Oymak, A. Khajehnejad and B. Hassibi, ``Recovery Threshold for Optimal Weight $\ell_1$ Minimization,'' International Symposium on Information Theory (ISIT) 2012, Cambridge, MA, PDF.
  • A. K. Krishnaswamy, , S. Oymak, and B. Hassibi. "A simpler approach to weighted ℓ 1 minimization." ICASSP 2012.
  • C. T. Li, S. Oymak, and B. Hassibi. "Deterministic phase guarantees for robust recovery in incoherent dictionaries." Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on. IEEE, 2012.
  • S. Oymak, K. Mohan, M. Fazel, and B. Hassibi, ``A Simplified Approach to Recovery Conditions for Low Rank Matrices,'' ISIT 2011, St. Petersburg, Russia, arXiv:1103.1178.
  • Samet Oymak, M. Amin Khajehnejad, and B. Hassibi. ``Weighted compressed sensing and rank minimization.'' ICASSP 2011.
  • M. Chowdhury, S. Oymak, M. A. Khajehnejad, & B. Hassibi Robustness Analysis of a List Decoding Algorithm for Compressed Sensing ICASSP 2011.

    Dimensionality reduction and Embedding techniques

    • S. Oymak, ``Near-optimal sample complexity bounds for circulant binary embedding,'' Feb. 2016 short version to appear at ICASSP 2017.
    • S. Oymak, and J. Tropp, ``Universality laws for randomized dimension reduction, with applications,'' manuscript Dec 2015.
    • S. Oymak, B. Recht, and M. Soltanolkotabi, ``Isometric sketching of any set via the Restricted Isometry Property,'' under revision Dec 2016.
    • S. Oymak and Ben Recht, ``Near optimal bounds for binary embeddings of arbitrary sets,'' manuscript Dec 2015.
    • S. Oymak and B. Hassibi, ``The proportional mean decomposition: A bridge between the Gaussian and bernoulli ensembles'' ICASSP 2015.
    • S. Oymak, A. Khajehnejad, and B. Hassibi, ``Subspace Expanders and Matrix Rank Minimization,'' ISIT 2011, PDF.
    • S. Oymak and B. Hassibi, ``New Null Space Results and Recovery Thresholds for Matrix Rank Minimization,'' partial results appeared in ISIT 2011, technical report arXiv:1011.6326.

      Graph processing

      • X. Pan, D. Papailiopoulos, S. Oymak, B. Recht, K. Ramchandran, & M. I. Jordan ``Parallel Correlation Clustering on Big Graphs,'' NIPS 2015.
      • R. Korlakai Vinayak, S. Oymak, and B. Hassibi, ``Sharp Performance Bounds for Graph Clustering via Convex Optimization,'' ICASSP 2014, full report.
        • R. Korlakai Vinayak, S. Oymak, and B. Hassibi, ``Graph Clustering With Missing Data: Convex Algorithms and Analysis.,'' NIPS 2014.
        • S. Oymak and B. Hassibi, ``Finding Dense Clusters via Low Rank + Sparse Decomposition,'' related results appeared at ICASSP 2014, NIPS 2014 technical report.

          Nonlinear models / Phase retrieval

          • K. Jaganathan, S. Oymak, and B. Hassibi, ``Sparse Phase Retrieval: Uniqueness Guarantees and Recovery Algorithms,'' accepted to Transactions on Signal Processing Aug. 2016, arXiv:1311.2745.
          • K. Jaganathan, S. Oymak, and B. Hassibi, ``Sparse Phase Retrieval: Convex Algorithms and Limitations,'' appeared in ISIT 2013, arXiv:1303.4128, code.
          • K. Jaganathan, S. Oymak, and B. Hassibi, ``On Robust Phase Retrieval for Sparse Signals,'' Allerton 2012, UIUC, Monticello, IL, PDF.
          • K. Jaganathan, S. Oymak, and B. Hassibi, ``Recovery of Sparse 1-D Signals from the Magnitudes of their Fourier Transform,'' ISIT 2012, arXiv:1206.1405, code.
          • K. Jaganathan, S. Oymak, and B. Hassibi, ``Phase Retrieval for Sparse Signals Using Rank Minimization,'' ICASSP 2012, PDF.