Now showing items 29667-29686 of 34872

    • Sparse optimization for robust and efficient loop closing 

      Latif, Yasir; Huang, Guoquan; Leonard, John Joseph; Neira, José (Elsevier BV, 2017-04)
      It is essential for a robot to be able to detect revisits or loop closures for long-term visual navigation. A key insight explored in this work is that the loop-closing event inherently occurs sparsely, i.e., the image ...
    • Sparse Projections of Medical Images onto Manifolds 

      Chen, George; Wachinger, Christian; Golland, Polina (Springer-Verlag Berlin Heidelberg, 2013)
      Manifold learning has been successfully applied to a variety of medical imaging problems. Its use in real-time applications requires fast projection onto the low-dimensional space. To this end, out-of-sample extensions are ...
    • Sparse Quantum Codes from Quantum Circuits 

      Bacon, Dave; Flammia, Steven T.; Harrow, Aram W.; Shi, Jonathan (Association for Computing Machinery (ACM), 2015-06)
      Sparse quantum codes are analogous to LDPC codes in that their check operators require examining only a constant number of qubits. In contrast to LDPC codes, good sparse quantum codes are not known, and even to encode a ...
    • Sparse Recovery for Earth Mover Distance 

      Gupta, Rishi V.; Indyk, Piotr; Price, Eric C. (University of Ilinois at Urbana-Champaign, 2010-09)
      We initiate the study of sparse recovery problems under the Earth-Mover Distance (EMD). Specically, we design a distribution over m x n matrices A, for m << n, such that for any x, given Ax, we can recover a k-sparse ...
    • Sparse Recovery Using Sparse Matrices 

      Gilbert, Anna; Indyk, Piotr (Institute of Electrical and Electronics Engineers, 2010-06)
      In this paper, we survey algorithms for sparse recovery problems that are based on sparse random matrices. Such matrices has several attractive properties: they support algorithms with low computational complexity, and ...
    • Sparse recovery with partial support knowledge 

      Do Ba, Khanh; Indyk, Piotr (Springer Berlin / Heidelberg, 2011-08)
      The goal of sparse recovery is to recover the (approximately) best k-sparse approximation [ˆ over x] of an n-dimensional vector x from linear measurements Ax of x. We consider a variant of the problem which takes into ...
    • Sparse Sensing and DMD-Based Identification of Flow Regimes and Bifurcations in Complex Flows 

      Kramer, Boris; Grover, Piyush; Boufounos, Petros; Nabi, Saleh; Benosman, Mouhacine (Society for Industrial and Applied Mathematics, 2017-06)
      We present a sparse sensing framework based on dynamic mode decomposition (DMD) to identify flow regimes and bifurcations in large-scale thermofluid systems. Motivated by real-time sensing and control of thermal-fluid flows ...
    • Sparse sensing for resource-constrained depth reconstruction 

      Ma, Fangchang; Carlone, Luca; Ayaz, Ulas; Karaman, Sertac (Institute of Electrical and Electronics Engineers (IEEE), 2016-12)
      We address the following question: is it possible to reconstruct the geometry of an unknown environment using sparse and incomplete depth measurements? This problem is relevant for a resource-constrained robot that has to ...
    • Sparse sign-consistent Johnson–Lindenstrauss matrices: Compression with neuroscience-based constraints 

      Allen-Zhu, Zeyuan; Gelashvili, Rati; Micali, Silvio; Shavit, Nir N. (National Academy of Sciences (U.S.), 2014-11)
      Johnson–Lindenstrauss (JL) matrices implemented by sparse random synaptic connections are thought to be a prime candidate for how convergent pathways in the brain compress information. However, to date, there is no complete ...
    • Sparse signal recovery and acquisition with graphical models 

      Cevher, Volkan; Indyk, Piotr; Carin, Lawrence; Baraniuk, Richard G. (Institute of Electrical and Electronics Engineers (IEEE), 2010-11)
      A great deal of theoretic and algorithmic research has revolved around sparsity view of signals over the last decade to characterize new, sub-Nyquist sampling limits as well as tractable algorithms for signal recovery from ...
    • Sparse spectral estimation from point process observations 

      Miran, Sina; Purdon, Patrick L.; Babadi, Behtash; Brown, Emery Neal (Institute of Electrical and Electronics Engineers (IEEE), 2017-06)
      We consider the problem of estimating the power spectral density of the neural covariates underlying the spiking of a neuronal population. We assume the spiking of the neuronal ensemble to be described by Bernoulli statistics. ...
    • Sparse sums of squares on finite abelian groups and improved semidefinite lifts 

      Fawzi, Hamza; Saunderson, James F; Parrilo, Pablo A (Springer Berlin Heidelberg, 2016-01)
      Let G be a finite abelian group. This paper is concerned with nonnegative functions on G that are sparse with respect to the Fourier basis. We establish combinatorial conditions on subsets S and T of Fourier basis elements ...
    • Sparsification of RNA structure prediction including pseudoknots 

      Mohl, Mathias; Salari, Raheleh; Will, Sebastian; Backofen, Rolf; Sahinalp, S. Cenk (BioMed Central Ltd, 2010-12)
      Abstract Background Although many RNA molecules contain pseudoknots, computational prediction of pseudoknotted RNA structure is still in its infancy due to high running time and space consumption implied by the dynamic ...
    • A Sparsity Detection Framework for On–Off Random Access Channels 

      Fletcher, Alyson K.; Rangan, Sundeep; Goyal, Vivek K. (Society of Photo-optical Instrumentation Engineers, 2009-09)
      This paper considers a simple on-off random multiple access channel, where n users communicate simultaneously to a single receiver over m degrees of freedom. Each user transmits with probability lambda, where typically ...
    • Sparsity Maximization under a Quadratic Constraint with Applications in Filter Design 

      Wei, Dennis; Oppenheim, Alan V. (Institute of Electrical and Electronics Engineers, 2010-06)
      This paper considers two problems in sparse filter design, the first involving a least-squares constraint on the frequency response, and the second a constraint on signal-to-noise ratio relevant to signal detection. It is ...
    • Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing 

      Cetin, Mujdat; Stojanovic, Ivana; Onhon, Ozben; Varshney, Kush; Samadi, Sadegh; e.a. (Institute of Electrical and Electronics Engineers (IEEE), 2014-06)
      This article presents a survey of recent research on sparsity-driven synthetic aperture radar (SAR) imaging. In particular, it reviews 1) the analysis and synthesis-based sparse signal representation formulations for SAR ...
    • Sparsity-Promoting Calibration for GRAPPA Accelerated Parallel MRI Reconstruction 

      Weller, Daniel S.; Polimeni, Jonathan R.; Grady, Leo; Wald, Lawrence L.; Adalsteinsson, Elfar; e.a. (Institute of Electrical and Electronics Engineers (IEEE), 2013-06)
      The amount of calibration data needed to produce images of adequate quality can prevent auto-calibrating parallel imaging reconstruction methods like generalized autocalibrating partially parallel acquisitions (GRAPPA) ...
    • SPASM and Twitch Domains in S-Adenosylmethionine (SAM) Radical Enzymes 

      Goldman, Peter J.; Drennan, Catherine L.; Grell, Tsehai Ariane (American Society for Biochemistry and Molecular Biology (ASBMB), 2014-12)
      S-Adenosylmethionine (SAM, also known as AdoMet) radical enzymes use SAM and a [4Fe-4S] cluster to catalyze a diverse array of reactions. They adopt a partial triose-phosphate isomerase (TIM) barrel fold with N- and ...
    • Spatial and temporal colonization dynamics of segmented filamentous bacteria is influenced by gender, age and experimental infection with Helicobacter hepaticus in Swiss Webster mice 

      Ge, Zhongming; Feng, Yan; Woods, Stephanie; Fox, James G (Elsevier, 2014-10)
      In this study, we examined colonization dynamics of segmented filamentous bacteria (SFB) in intestine of Swiss Webster (SW) mice infected with Helicobacter hepaticus (Hh). At 8 weeks post-inoculation with Hh (WPI), cecal ...
    • Spatial and Temporal Patterns in Large-Scale Traffic Speed Prediction 

      Asif, Muhammad Tayyab; Dauwels, Justin; Oran, Ali; Fathi, Esmail; Dhanya, Menoth Mohan; e.a. (Institute of Electrical and Electronics Engineers (IEEE), 2014-04)
      The ability to accurately predict traffic speed in a large and heterogeneous road network has many useful applications, such as route guidance and congestion avoidance. In principle, data-driven methods, such as support ...