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