**SAHD 2015**

**July 27-29, 2015**

*Ken Bollen*
- The Latent Variable - ALT (LV-ALT) model: a general framework for longitudinal data analysis

*Alex Bronstein*
- Graph matching: relax or not?

*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

*Yonina Eldar*
- Sub-Nyquist sampling without sparsity

*Surya Ganguli*
- A theory of neural dimensionality, dynamics, and measurement

*Babak Hassibi*
- LASSO with nonlinear measurements

*Al Hero*
- Correlation mining from massive data: high dimensional sampling regimes

*Tony Jebara*
- Graphical modeling with the Bethe approximation

*Marina Meila*
- Modeling ordered data by counting inversions

*Andrea Montanari*
- Semidefinite programming relaxations for graph estimation

*Stan Osher*
- How sparsity and L1 optimization impacts "continuous" applied mathematics, physics and engineering

*John Paisley*
- Scalable Bayesian nonparametric dictionary learning

*Pradeep Ravikumar*
- Elementary estimators for "big-p" statistical models

*
Cynthia Rudin*
- Sparse if-then rule models

*Phil Schniter*
- Iteratively reweighted $\ell_1$ approaches to sparse composite regularization

*James Scott*
- False discovery rate smoothing

*Marc Suchard*
- High-dimensional biological sequences through simple models and posterior diagnostics

*Jared Tanner*
- Parallel-$\ell_0$, a fully parallel algorithm for combinatorial compressed sensing

*Joel Tropp*
- Applied random matrix theory

*David Wipf*
- Non-Convex, Bayesian-inspired algorithms for sparse and low-rank estimation