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- Spring 2009 ECE 379 Introduction to Signals & Information Processing
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- Adaptive Hausdorff Estimation of Density Level Sets
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- De Novo Signaling Pathway Reconstruction From Multiple
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- Sample Complexity for 1-bit Compressed Sensing and Sparse Classification
- On the Success of Network Topology Inference using a Markov Random Walk Model for Nested Routing Policies
- OPTIMAL WEIGHTED HIGHPASS FILTERS USING MULTISCALE ANALYSIS
- Template Learning from Atomic Representations: A Wavelet-based
- Wavelet-Based Transformations for Nonlinear Signal Processing
- Dimensionality Reduction: beyond the Johnson-Lindenstrauss Yair Bartal
- University of California Los Angeles
- A Restricted Isometry Property for Structurally-Subsampled Unitary Matrices
- Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
- SUBMITTED FOR PUBLICATION; 2007. 1 Gradient Projection for Sparse
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- SUBMITTED FOR PUBLICATION; 2007. 1 Majorization-Minimization Algorithms for
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- Matched Source-Channel Communication for Field Estimation in Wireless Sensor Networks
- arXiv:1001.5311v1[math.ST]29Jan2010 DISTILLED SENSING: ADAPTIVE SAMPLING FOR
- Finite sample analysis of semi-supervised learning Technical Report ECE-08-03
- !#"%$&'()10 23$& 45687 9@A0 BCD$E4 BF41 G !D5@HD45" D4 IP45Q$& R SUT $&'VW
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- Minimax Optimal Level Set Estimation R. M. Willett, Member, IEEE, and R. D. Nowak, Senior Member, IEEE
- Backcasting: Adaptive Sampling for Sensor Networks Rebecca Willett, Aline Martin, and Robert Nowak
- Minimax Bounds for Active Learning Rui M. Castro1,2
- Necessary and Sufficient Conditions for Success of the Nuclear Norm Heuristic for Rank Minimization
- Causal Network Inference via Group Sparse Regularization
- Reputation-based Framework for High Integrity Sensor Networks
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- Space-Time Sparse Reconstruction for Magneto-/Electroencephalography
- Network Mapping and Measurement Conference 2011 Madison, Wisconsin
- Multi-Manifold Semi-Supervised Learning Computer Sciences Dept.
- Distributed Optimization in Sensor Networks Michael Rabbat and Robert Nowak
- Online Identification and Tracking of Subspaces from Highly Incomplete Information
- Blind Calibration of Sensor Networks Laura Balzano
- Active Sensing What is Active Sensing?
- Random Features for Large-Scale Kernel Machines Ali Rahimi and Ben Recht
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- Transduction with Matrix Completion: Three Birds with One Stone
- Sparse Interactions: Identifying High-Dimensional Multilinear Systems via Compressed Sensing
- High-Dimensional Matched Subspace Detection When Data are Missing
- Active Sensing and Learning Rui Castro and Robert Nowak
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- Improved Approach to Lidar Airport Obstruction Surveying Using Full-Waveform Data
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- Journal of Machine Learning Research x (2006) xx Submitted 9/05; Published xx/xx Learning Minimum Volume Sets
- Network Radar: Tomography from Round Trip Time Measurements
- Multiple Source, Multiple Destination Network Tomography
- Sequential Monte Carlo Inference of Internal Delays in Nonstationary Communication Networks
- Designing Wireless Sensor Networks as a Shared Resource for Sustainable Development
- Design, Analysis, and Implementation of DVSR: A Fair, High Performance Protocol for Packet Rings
- Rapid Deployment with Confidence: Calibration and Fault Detection in Environmental Sensor Networks
- Parallel Stochastic Gradient Algorithms for Large-Scale Matrix Benjamin Recht and Christopher Re
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- Accepted Manuscript Probability of Unique Integer Solution to a System of Linear Equations
- Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning
- Unsupervised Regression with applications to Nonlinear System Identification
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- ECE 830 Fall 2010 Statistical Signal Processing instructor: R. Nowak , scribe: J. Jiao
- Crystallography Project --Final Goals and Objectives Due Sunday, May 1, 2005
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- Tensor completion and low-n-rank tensor recovery via convex optimization
- Crystallography Project --Task 1 Due Sunday March 27
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- Estimating Inhomogeneous Fields Using Wireless Sensor Networks
- Learning Minimum Volume Sets Clayton Scott
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- Characterizing Decoding Robustness under Parametric Channel Uncertainty
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- The Geometry of Generalized Binary Search Robert D. Nowak
- Tight Measurement Bounds for Exact Recovery of Structured Sparse Signals
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- Active Ranking using Pairwise Comparisons Kevin G. Jamieson
- Tight Clustering Condition 1. Introduction 3. Efficient Hierarchical Clustering
- GAUTAM DASARATHY dasarathy@wisc.edu 2110 University Avenue, Apt. #110
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- arXiv:submit/0431972[cs.IT]8Mar2012 Near-Optimal Compressive Binary Search
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- k-Subspaces with Missing Data University of Wisconsin Technical Report ECE-11-02
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