Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization
By Tyler B. Johnson, Carlos Guestrin. 2015
65 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Virginia Smith
- Jakub Konecný
- Martin Jaggi
- Chenxin Ma
- Peter Richtárik
- Martin Takác
- Simone Forte
- Francis R. Bach
Citations in the corpus
- CoCoA: A General Framework for Communication-Efficient Distributed Optimization (2016, methodology): “For the L 1 examples discussed, existing fast L 1 -solvers for the single-machine case, such as glmnet variants (Friedman et al., 2010) or blitz (Johnson and Guestrin, 2015) can be directly applied to each local subproblem ) within Algorithm 1.”
- Faster Coordinate Descent via Adaptive Importance Sampling (2017, background): “For general convex regularizers such as L1, the development of CD algorithms includes [Fu, 1998, Friedman et al., 2007, 2010] and more recent extensions also improving the theoretical convergence rates [Shalev-Shwartz and Tewari, 2011, Johnson and Guestrin, 2015, Zhao et al., 2014].”
- L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework (2015, methodology): “Therefore, existing fast L1-solvers for the single-machine case, such as GLMNET variants [11] or BLITZ [13] can be directly applied to each local subproblem Gσ′k ( · ;v,α[k]) within Algorithm 1.”