Richard Peng
where else to find them
no profile links on file
what they talk about
all 4 in the filters
where they keep going back
no series more than once — all 4 in the filters
on a stage with
- Billy Jinonce
- David Williamsononce
- Monika Henzingeronce
who talks about the same things
nobody close enough yet
| title | conference | date |
|---|---|---|
| A Combinatorial Cut-Toggling Algorithm for Solving Laplacian Linear Systems | ITCS 2023 | 2023-01-10 |
Introduces a dual cut-toggling algorithm for solving Lx = b that mirrors KOSZ: it maintains vertex potentials on a low-stretch spanning tree, samples… | ||
| Scalable Algorithmic Primitives for Data Science | Randomized Numerical Linear Algebra and Applications 2018 | 2018-09-24 |
Argues that solving graph-structured linear systems becomes practical by combining preconditioning, randomized row sampling and combinatorial sparsifiers… | ||
| L_p Row Sampling by Lewis Weights | Fast Algorithms via Spectral Methods 2014 | 2014-12-01 |
Claims a practical method to sample rows so A' preserves ||Ax||_p for all x by sampling with Lewis weights, shows existence and fast computation, and proves L1… | ||
| Cut-Approximators, Approximating Undirected Max Flows, and Recursion | Fast Algorithms via Spectral Methods 2014 | 2014-12-01 |
Presents a concrete recursive recipe that yields a nearly‑linear time (1+ε)-approximation for undirected max flow by combining alpha cut approximator trees… | ||
| An Efficient Parallel Solver for SDD Linear Systems | Spectral Algorithms: From Theory to Practice 2014 | 2014-10-27 |
Presents an algorithm that solves SDD (graph Laplacian) systems with nearly-linear work and polylog depth by building an “approximate inverse chain”… | ||
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