# Agenda

A preliminary version of the technical program is now available.

Below are useful links regarding the technical program.

- Featured talks titles and abstracts
- Whiteboard/Poster session titles (also listed below) Note: Posters will be attached to the whiteboards, which are 65 inches wide and 36 inches tall.
- Technical Program

## Monday, July 27

### 09:15 - 09:30 Welcome

### 09:30 - 11:30 Invited Talks I

- Stan Osher -
*How sparsity and L1 optimization impacts "continuous" applied mathematics, physics and engineering* - Phil Schniter -
*Iteratively reweighted L1 approaches to sparse composite regularization* - Volkan Cevher -
*A universal primal-dual convex optimization framework* - Yuxin Chen -
*Solving random quadratic systems of equations is nearly as easy as solving linear systems*

### 11:30 - 12:30 Whiteboards I

### 12:30 - 13:30 Lunch

### 13:30 - 15:30 Invited Talks II

- Jared Tanner -
*Parallel-L0, a fully parallel algorithm for combinatorial compressed sensing* - Babak Hassibi -
*LASSO with nonlinear measurements* - Joel Tropp -
*Applied random matrix theory* - Yonina Eldar -
*Sub-Nyquist sampling without sparsity*

### 15:30 - 17:00 Posters I

## Tuesday, July 28

### 09:00 - 10:30 Invited Talks III

- Cynthia Rudin -
*Sparse if-then rule models* - David Wipf -
*Non-Convex, Bayesian-inspired algorithms for sparse and low-rank estimation* - John Paisley -
*Scalable Bayesian nonparametric dictionary learning*

### 10:30 - 11:00 Coffee Break

### 11:00 - 12:00 Invited Talks IV

- Alex Bronstein -
*Graph matching: relax or not?* - Ken Bollen -
*The Latent Variable - Autoregressive Latent Trajectory (LV-ALT) model: a general framework for longitudinal data analysis*

### 12:00 - 13:00 Whiteboards II

### 12:30 - 13:30 Lunch

### 13:30 - 15:30 Invited Talks V

- Patrick Wolfe -
*Network analysis and nonparametric statistics* - Pradeep Ravikumar -
*Elementary estimators for “big-p” statistical models* - Marc Suchard -
*High-dimensional biological sequences through simple models and posterior diagnostics* - James Scott -
*False discovery rate smoothing*

### 15:30 - 17:00 Posters II

### 19:00 - 22:00 Workshop banquet

## Wednesday, July 29

### 09:00 - 10:30 Invited Talks VI

- Andrea Montanari -
*Semidefinite programming relaxations for graph estimation* - Alfred Hero -
*Correlation mining from massive data: high dimensional sampling regimes* - Marina Meila -
*Modeling ordered data by counting inversions*

### 10:30 - 11:00 Coffee Break

### 11:00 - 12:00 Invited Talks VII

- Tony Jebara -
*Graphical modeling with the Bethe approximation* - Surya Ganguli -
*A theory of neural dimensionality, dynamics, and measurement*

## Whiteboard Session I (Monday, July 27 from 11:30 am - 12:30 pm)

- Pallavi Basu -
*Model Selection in High-Dimensional Misspecified Models* - Miles Lopes -
*Compressed Sensing without Sparsity Assumptions* - Henry Pfister -
*Connections Between Coding and Compressed Sensing* - Farhad Pourkamali-Anaraki -
*Efficient PCA for large high-dimensional datasets via Randomized Sketching* - Galen Reeves -
*Scalable Approximations of Marginal Posteriors in Variable Selection* - Rebecca Willett -
*Learning Single Index Models in High Dimensions*

## Whiteboard Session II (Tuesday, July 28 from 12:00 - 1:00 pm)

- Ingrid Daubechies -
*ConceFT: Concentration in Frequency and Time* - Kai Fan -
*Hierarchical Graph-Coupled HMMs for Heterogeneous Personalized Health Data* - Raja Giryes -
*Theoretical Limits in Sparsity and Deep Learning* - Sayan Mukherjee -
*Learning mixtures of subspaces* - Manolis Tsakiris -
*Abstract Algebraic Subspace Clustering* - Sergey Voronin -
*Randomized blocked algorithms for efficiently computing rank-revealing factorizations of matrices*

## Poster Session I (Monday, July 27 from 3:30 - 5:00 pm)

## Last name M - Z

- Yanting Ma -
*Universal Denoising in Approximate Message Passing* - Sorin Mitran -
*Information geometry and model reduction* - Ikenna Odinaka -
*Spectrally Grouped Edge-Preserving Reconstruction* - Qiang Qiu -
*Random Forests Can Hash* - Qing Qu -
*Complete Dictionary Learning Over the Sphere* - Akshay Rangamani -
*Learning Program Attributes in Control Flow Graphs* - Owen Rehrauer -
*Fluorescence Modeling for OB-CD Raman Spectroscopy* - Abhra Sarkar -
*Bayesian Nonparametric Higher Order Markov Chains* - Anand Sarwate -
*The performance of differentially private PCA* - Shahin Sefati -
*Linear Systems with Sparse Inputs* - Anish Simhal -
*Computational statistics for CLARITY volumes* - Catherine Stamoulis -
*Signal processing approaches for genomic data* - Charles Talbot -
*Reduced Stochastic Models of Permeable Medium Flow* - Mariano Tepper -
*Compressed NMF is Fast and Accurate* - Manolis Tsakiris -
*Abstract Algebraic Subspace Clustering* - Kyle Ulrich -
*Gaussian Process Kernels for Cross-Spectrum Analysis* - Sergey Voronin -
*An efficient algorithm for computing a CUR factorization* - Tong Wang -
*Bayesian Or’s of And’s for Interpretable Classification* - Yizhe Zhang -
*Spatial dependent deep factor model*

## Poster Session II (Tuesday, July 28 from 3:30 - 5:00 pm)

## Last name A - L

- Amit Ashok -
*Analysis & Simulation Framework: X-ray Threat Detection* - Martin Azizyan -
*Extreme Compressive Sampling for Covariance Estim.* - Dror Baron -
*Image Reconstruction in Radio Astronomy* - Evan Byrne -
*Sparse Multinomial Logistic Regression via AMP* - Dan Coroian -
*Learning a Personalized CDSS From EHR Data* - Jyotishka Datta -
*Bayesian Cluster Detection for Rare Variants* - Mauricio Delbracio -
*Burst Deblurring* - Lee Dicker -
*Efficient variance estimation for high-dimensional linear models* - Yan Feng -
*Model reduction of stochastic biomechanical system* - Raja Giryes -
*Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?* - Joel Greenberg -
*Coding and compression in snapshot XRD imaging* - Shermin Hamzehei -
*Compressive Parameter Estimation via AMP* - Jordan Hashemi -
*Pose-invariant cross-modality facial expression* - Alfred Hero -
*On the sample complexity of correlation mining* - Xin Jiang -
*Minimax Rates for Photon Limited Image Reconstruction* - Mojtaba Kadkhodaie -
*Locating Rare and Weak Material Anomalies by Convex Demixing of Propagating Wavefield Data* - Yan Kaganovsky -
*Variational Automatic Relevance Determination* - Yuehaw Khoo -
*NMR structural calculation via semidefinite programming* - Jinyoung Kim -
*Robust Prediction of DBS targeting structures* - Santhosh Kumar -
*Reed-Muller Codes Achieve Capacity on erasure Channels* - Yuanxin Li -
*Stable Super-Resolution of Mixture Models* - Mengke Lian -
*Belief-Propagation Reconstruction for Compressed Sensing: Quantization vs. Gaussian Approximation* - Luoluo Liu -
*Partial Face Recognition* - Miles Lopes -
*Compressed Sensing without Sparsity Assumptions* - John Lu -
*Optical imaging for forensics* - Yue Lu -
*Randomized Kaczmarz Algorithm and its Cousins: Exact MSE Analysis and Asymptotically Sharp Bounds*