News & Events

65 News items, Awards, Events or Talks found.


  •  NEWS    MERL Researcher appointed Senior Area Editor for IEEE Signal Processing Letters
    Date: February 11, 2014
    Where: IEEE Signal Processing Letters
    MERL Contact: Petros T. Boufounos
    Brief
    • Petros Boufounos was appointed as a Senior Area Editor of IEEE Signal Processing Letters.
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  •  NEWS    Signal Processing with Adaptive Sparse Structural Representation (SPARS): publication by Petros T. Boufounos
    Date: July 8, 2013
    Where: Signal Processing with Adaptive Sparse Structural Representation (SPARS)
    MERL Contact: Petros T. Boufounos
    Brief
    • The article "On Embedding the Angles Between Signals" by Boufounos, P.T. was published in Signal Processing with Adaptive Sparse Structural Representation (SPARS).
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  •  NEWS    International Conference on Sampling Theory and Applications (SampTA): publication by Petros T. Boufounos
    Date: July 1, 2013
    Where: International Conference on Sampling Theory and Applications (SampTA)
    MERL Contact: Petros T. Boufounos
    Brief
    • The paper "Sparse Signal Reconstruction from Phase-only Measurements" by Boufounos, P.T. was presented at the International Conference on Sampling Theory and Applications (SampTA).
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  •  EVENT    ICASSP 2013 - Student Career Luncheon
    Date & Time: Thursday, May 30, 2013; 12:30 PM - 2:30 PM
    Location: Vancouver, Canada
    MERL Contacts: Anthony Vetro; Petros T. Boufounos; Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • MERL is a sponsor for the first ICASSP Student Career Luncheon that will take place at ICASSP 2013. MERL members will take part in the event to introduce MERL and talk with students interested in positions or internships.
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  •  NEWS    ICASSP 2013: 9 publications by Jonathan Le Roux, Dehong Liu, Robert A. Cohen, Dong Tian, Shantanu D. Rane, Jianlin Guo, John R. Hershey, Shinji Watanabe, Petros T. Boufounos, Zafer Sahinoglu and Anthony Vetro
    Date: May 26, 2013
    Where: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
    MERL Contacts: Dehong Liu; Jianlin Guo; Anthony Vetro; Petros T. Boufounos; Jonathan Le Roux
    Brief
    • The papers "Stereo-based Feature Enhancement Using Dictionary Learning" by Watanabe, S. and Hershey, J.R., "Effectiveness of Discriminative Training and Feature Transformation for Reverberated and Noisy Speech" by Tachioka, Y., Watanabe, S. and Hershey, J.R., "Non-negative Dynamical System with Application to Speech and Audio" by Fevotte, C., Le Roux, J. and Hershey, J.R., "Source Localization in Reverberant Environments using Sparse Optimization" by Le Roux, J., Boufounos, P.T., Kang, K. and Hershey, J.R., "A Keypoint Descriptor for Alignment-Free Fingerprint Matching" by Garg, R. and Rane, S., "Transient Disturbance Detection for Power Systems with a General Likelihood Ratio Test" by Song, JX., Sahinoglu, Z. and Guo, J., "Disparity Estimation of Misaligned Images in a Scanline Optimization Framework" by Rzeszutek, R., Tian, D. and Vetro, A., "Screen Content Coding for HEVC Using Edge Modes" by Hu, S., Cohen, R.A., Vetro, A. and Kuo, C.C.J. and "Random Steerable Arrays for Synthetic Aperture Imaging" by Liu, D. and Boufounos, P.T. were presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
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  •  TALK    Communication/computation tradeoffs and other practical considerations in distributed convex optimization
    Date & Time: Thursday, March 21, 2013; 12:00 PM
    Speaker: Konstantinos Tsianos, McGill, Montreal, Canada
    MERL Host: Petros T. Boufounos
    Abstract
    • Distributed algorithms become necessary to employ the computational resources needed for solving the large scale optimization problems that arise in areas such as machine learning,computation biology and others. We study a very general distributed setting where the data is distributed over many machines that can communicate with one another over a network that does not have any specialized communication infrastructure. In this setting the role of the network becomes critical in the performance of a distributed algorithm. From a more theoretical standpoint we discuss two questions: 1) How many nodes should we use for a given problem before communication becomes a bottleneck? and 2) How often should the nodes communicate to one another for the communication cost to be worth the transmission? In addition, we discuss some more practical issue that one needs to consider in implementing algorithms that are asynchronous and robust to communication delays.
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  •  NEWS    DCC 2013: publication by Petros T. Boufounos and Shantanu D. Rane
    Date: March 20, 2013
    Where: Data Compression Conference (DCC)
    MERL Contact: Petros T. Boufounos
    Research Area: Computational Sensing
    Brief
    • The paper "Efficient Coding of Signal Distances Using Universal Quantized Embeddings" by Boufounos, P.T. and Rane, S. was presented at the Data Compression Conference (DCC).
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  •  NEWS    Journal of Machine Learning Research (JMLR): publication by Petros T. Boufounos and others
    Date: March 1, 2013
    Where: Journal of Machine Learning Research (JMLR)
    MERL Contact: Petros T. Boufounos
    Research Area: Computational Sensing
    Brief
    • The article "Greedy Sparsity-Constrained Optimization" by Bahmani, S., Raj, B. and Boufounos, P. was published in Journal of Machine Learning Research (JMLR).
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  •  NEWS    IEEE Signal Processing Magazine: 2 publications by Petros T. Boufounos and Shantanu D. Rane
    Date: February 13, 2013
    Where: IEEE Signal Processing Magazine
    MERL Contact: Petros T. Boufounos
    Brief
    • The articles "Privacy-Preserving Nearest Neighbor Methods: Comparing Signals without Revealing Them" by Rane, S. and Boufounos, P.T. and "Privacy-preserving Speech Processing: Cryptographic and String-Matching Frameworks Show Promise" by Pathak, M.A., Raj, B., Rane, S. and Samaragdis, P. were published in IEEE Signal Processing Magazine.
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  •  NEWS    IEEE Transactions on Information Theory: publication by Petros T. Boufounos and others
    Date: January 23, 2013
    Where: IEEE Transactions on Information Theory
    MERL Contact: Petros T. Boufounos
    Research Area: Computational Sensing
    Brief
    • The article "Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors" by Jacques, L., Laska, J.N., Boufounos, P.T. and Baraniuk, R.G. was published in IEEE Transactions on Information Theory.
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  •  NEWS    MMSP 2012: publication by Petros T. Boufounos, Shantanu D. Rane and others
    Date: September 17, 2012
    Where: IEEE International Workshop on Multimedia Signal Processing (MMSP)
    MERL Contact: Petros T. Boufounos
    Research Areas: Digital Video, Computational Sensing
    Brief
    • The paper "Quantized Embeddings of Scale-Invariant Image Features for Mobile Augmented Reality" by Li, M., Rane, S. and Boufounos, P. was presented at the IEEE International Workshop on Multimedia Signal Processing (MMSP).
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  •  AWARD    MMSP 2012 Top 10% Paper Award
    Date: September 1, 2012
    Awarded to: Mu Li, Shantanu Rane and Petros Boufounos
    Awarded for: "Quantized Embeddings of Scale-Invariant Image Features for Mobile Augmented Reality"
    Awarded by: IEEE International Workshop on Multimedia Signal Processing (MMSP)
    MERL Contact: Petros T. Boufounos
    Research Areas: Digital Video, Computational Sensing
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  •  NEWS    International Workshops APPROX/RANDOM 2012: publication by Petros T. Boufounos and others
    Date: August 15, 2012
    Where: International Workshops APPROX/RANDOM
    MERL Contact: Petros T. Boufounos
    Research Area: Computational Sensing
    Brief
    • The paper "What's the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid" by Boufounos, P., Cevher, V., Gilbert, A.C., Li, Y. and Strauss, M.J. was presented at the International Workshops APPROX/RANDOM.
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  •  TALK    Communication Systems for Oilfield Applications
    Date & Time: Tuesday, August 7, 2012; 12:00 PM
    Speaker: Dr. Julius Kusuma, Schlumberger-Doll Research
    MERL Host: Petros T. Boufounos
    Abstract
    • The oilfield is a rich area for research and engineering in communication and signal processing. Communication over non-standard channels, using constrained sources, noisy environments, and limited computational and energy resources, are some of the key challenges in this domain. In this talk I will give an introduction first on the role of science and technology, in particular communication and signal processing, in the oilfield. Due to its unique role in the industry, Schlumberger has a rich variety of communication systems over EM wireless, wired, acoustic, and even fluid pressure channels.

      In this talk we give a brief tour of some of the state-of-the-art and showcase how technology has revolutionized the practice of the industry, enabling innovations such as horizontal drilling, logging-while-drilling, and well-placement. At the same time, we give a tutorial on how the lifecycle of a reservoir is managed, including imaging, drilling, logging, sampling, testing, and completing. Throughout, we will show how communication has revolutionized the practice in the industry.
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  •  NEWS    IGARSS 2012: publication by Petros T. Boufounos and Dehong Liu
    Date: July 22, 2012
    Where: IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
    MERL Contacts: Dehong Liu; Petros T. Boufounos
    Research Areas: Digital Video, Computational Sensing
    Brief
    • The paper "Pan-Sharpening with Multi-scale Wavelet Dictionary" by Liu, D. and Boufounos, P.T. was presented at the IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
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  •  TALK    Sparse projections onto convex sets
    Date: Tuesday, July 3, 2012
    Speaker: Prof. Volkan Cevher, EPFL
    MERL Host: Petros T. Boufounos
    Abstract
    • Many natural and man-made signals exhibit a few degrees of freedom relative to their dimension due to natural parameterizations or constraints. The inherent low-dimensional structure of such signals are mathematically modeled via combinatorial and geometric concepts, such as sparsity, unions-of-subspaces, or spectral sets, and are now revolutionizing the way we address linear inverse problems from incomplete data.

      In this talk, we describe a set of structured sparse models for constrained linear inverse problems that feature exact and epsilon-approximate projections in polynomial time. We pay particular attention to the sparsity models based on matroids, multi-knapsack, and clustering as well as spectrally constrained models. We then study sparse projections onto convex sets, such as the (general) simplex, and ell-1,2,inf balls. Finally, we describe a hybrid optimization framework which explicitly leverages these non-convex models along with additional convex constraints to obtain better recovery performance in compressive sensing, learn interpretable sparse densities from finite samples, and improved sparse Markowitzs portfolios with better return/cost performance.
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  •  NEWS    ICASSP 2012: 8 publications by Petros T. Boufounos, Dehong Liu, John R. Hershey, Jonathan Le Roux and Zafer Sahinoglu
    Date: March 25, 2012
    Where: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
    MERL Contacts: Dehong Liu; Jonathan Le Roux; Petros T. Boufounos
    Brief
    • The papers "Dictionary Learning Based Pan-Sharpening" by Liu, D. and Boufounos, P.T., "Multiple Dictionary Learning for Blocking Artifacts Reduction" by Wang, Y. and Porikli, F., "A Compressive Phase-Locked Loop" by Schnelle, S.R., Slavinsky, J.P., Boufounos, P.T., Davenport, M.A. and Baraniuk, R.G., "Indirect Model-based Speech Enhancement" by Le Roux, J. and Hershey, J.R., "A Clustering Approach to Optimize Online Dictionary Learning" by Rao, N. and Porikli, F., "Parametric Multichannel Adaptive Signal Detection: Exploiting Persymmetric Structure" by Wang, P., Sahinoglu, Z., Pun, M.-O. and Li, H., "Additive Noise Removal by Sparse Reconstruction on Image Affinity Nets" by Sundaresan, R. and Porikli, F. and "Depth Sensing Using Active Coherent Illumination" by Boufounos, P.T. were presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
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  •  NEWS    IEEE Transactions on Information Theory: publication by Petros T. Boufounos
    Date: February 27, 2012
    Where: IEEE Transactions on Information Theory
    MERL Contact: Petros T. Boufounos
    Research Area: Computational Sensing
    Brief
    • The article "Universal Rate-Efficient Scalar Quantization" by Boufounos, P.T. was published in IEEE Transactions on Information Theory.
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  •  NEWS    WIFS 2011: publication by Petros T. Boufounos and Shantanu D. Rane
    Date: November 29, 2011
    Where: IEEE International Workshop on Information Forensics and Security (WIFS)
    MERL Contact: Petros T. Boufounos
    Research Area: Information Security
    Brief
    • The paper "Secure Binary Embeddings for Privacy Preserving Nearest Neighbors" by Boufounos, P. and Rane, S. was presented at the IEEE International Workshop on Information Forensics and Security (WIFS).
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  •  NEWS    ACSSC 2011: publication by Petros T. Boufounos and others
    Date: November 6, 2011
    Where: Asilomar Conference on Signals, Systems and Computers (ACSSC)
    MERL Contact: Petros T. Boufounos
    Research Area: Computational Sensing
    Brief
    • The paper "Greedy Sparsity-Constrained Optimization" by Bahmani, S., Boufounos, P. and Raj, B. was presented at the Asilomar Conference on Signals, Systems and Computers (ACSSC).
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  •  NEWS    Applied and Computational Harmonic Analysis: publication by Petros T. Boufounos and others
    Date: November 1, 2011
    Where: Applied and Computational Harmonic Analysis
    MERL Contact: Petros T. Boufounos
    Research Area: Computational Sensing
    Brief
    • The article "Democracy in Action: Quantization, Saturation and Compressive Sensing" by Laska, J.N., Boufounos, P.T., Davenport, M.A. and Baraniuk, R.G. was published in Applied and Computational Harmonic Analysis.
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  •  NEWS    ICIP 2011: 4 publications by Matthew E. Brand, Petros T. Boufounos, Shantanu D. Rane, Anthony Vetro and Dong Tian
    Date: September 11, 2011
    Where: IEEE International Conference on Image Processing (ICIP)
    MERL Contacts: Matthew Brand; Anthony Vetro; Petros T. Boufounos
    Brief
    • The papers "Distributed Compression of Zerotrees of Wavelet Coefficients" by Wang, Y., Rane, S., Boufounos, P. and Vetro, A., "A Trellis-based Approach for Robust View Synthesis" by Tian, D., Vetro, A. and Brand, M., "Concentric Ring Signature Descriptor for 3D Objects" by Nguyen, H.V. and Porikli, F. and "Parallel Quadratic Programming for Image Processing" by Brand, M. and Chen, D. were presented at the IEEE International Conference on Image Processing (ICIP).
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  •  NEWS    IGARSS 2011: publication by Petros T. Boufounos and Dehong Liu
    Date: July 24, 2011
    Where: IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
    MERL Contacts: Dehong Liu; Petros T. Boufounos
    Research Area: Computational Sensing
    Brief
    • The paper "High Resolution SAR Imaging Using Random Pulse Timing" by Liu, D. and Boufounos, P.T. was presented at the IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
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  •  TALK    Gigapixel Binary Sensing: Image Acquisition Using Oversampled One-Bit Poisson Statistics
    Date & Time: Wednesday, June 15, 2011; 12:00 PM
    Speaker: Dr. Yue M. Lu, Harvard School of Engineering and Applied Sciences
    MERL Host: Petros T. Boufounos
    Abstract
    • Before the advent of digital image sensors, photography, for the most part of its history, used film to record light information. In this talk, I will present a new digital image sensor that is reminiscent of photographic film. Each pixel in the sensor has a binary response, giving only a one-bit quantized measurement of the local light intensity.

      To analyze its performance, we formulate the binary sensing scheme as a parameter estimation problem based on quantized Poisson statistics. We show that, with a single-photon quantization threshold and large oversampling factors, the Cramer-Rao lower bound of the estimation variance approaches that of an ideal unquantized sensor, that is, as if there were no quantization in the sensor measurements. Furthermore, this theoretical performance bound is shown to be asymptotically achievable by practical image reconstruction algorithms based on maximum likelihood estimators.

      Numerical results on both synthetic data and images taken by a prototype sensor verify the theoretical analysis and the effectiveness of the proposed image reconstruction algorithm. They also demonstrate the benefit of using the new binary sensor in applications involving high dynamic range imaging.

      Joint work with Feng Yang, Luciano Sbaiz and Martin Vetterli.
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  •  TALK    Recursive Sparse Recovery and Applications in Dynamic Imaging
    Date & Time: Friday, June 3, 2011; 11:00 AM
    Speaker: Prof. Namrata Vaswani, Iowa State University
    MERL Host: Petros T. Boufounos
    Abstract
    • In this talk, I will discuss our recent work on Recursive Sparse Recovery (RecSparsRec) and show how it provides novel solutions to two very different problems in dynamic imaging. RecSparsRec refers to recursive approaches to causally recover a time sequence of signals/images from a greatly reduced number of measurements (compared to existing approaches), by utilizing their sparsity.

      The motivating application for RecSparsRec is fast recursive dynamic magnetic resonance imaging (MRI) for real-time applications like MRI-guided surgery. MRI is a technique for cross-sectional imaging that acquires Fourier projections of the cross-section to be reconstructed, one-at-a-time. Thus, the ability to accurately reconstruct using fewer measurements directly translates into reduced scan times. This, along with online (causal) and fast (recursive) reconstruction algorithms, can enable real-time imaging of fast changing physiological phenomena, and thus make real-time MRI feasible. Cross-sectional images of the brain, heart, or other organs are known to be wavelet sparse. Our recent work was the first to observe that, in a time sequence, their sparsity pattern changes quite slowly. Using this fact, we were able to reformulate the RecSparsRec problem as one of sparse reconstruction with partially known support. We introduced a simple, but very powerful, approach called!
      Modified-CS that achieves provably exact reconstruction (in the noise-free case) and whose error is provably stable over time (in the noisy case), with using much fewer measurements than existing work. Our preliminary experiments indicate that Modified-CS needs roughly 5-times fewer measurements than existing MR scanner technology and 1.5-times fewer than existing research literature.

      I will briefly also discuss our ongoing work on the difficult video analysis problem of separating foreground moving objects from a background scene that is itself is changing and dong this in real-time. This can be posed as a recursive robust principal components analysis (PCA) problem in the presence of correlated sparse outliers or equivalently, as a problem of recursive sparse recovery in the presence of very large, but ``low rank" noise (noise with a low rank covariance matrix).
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