Moses Charikar
where else to find them
what they talk about
where they keep going back
no series more than once — all 8 in the filters
on a stage with
- Deborah M. Gordononce
- Kirankumar Shiraguronce
- Shivam Gargonce
who talks about the same things
nobody close enough yet
| title | conference | date |
|---|---|---|
| Sketching Techniques for Kernel Density Estimation | Sketching and Algorithm Design 2023 | 2023-10-09 |
Presents concrete algorithms that turn kernel density estimation into a sketching data structure using locality-sensitive hashing for distance-biased sampling… | ||
| A New Model for Ant Trail Formation and its Convergence Properties | ITCS 2021 | 2021-01-06 |
A flow-based pheromone model on directed graphs is defined with decay, node leakage and forward/backward unit flows and a linear decision rule; for two… | ||
| Importance Sampling in High Dimensions via Hashing | Sublinear Algorithms and Nearest-Neighbor Search | 2018-11-27 |
Shows a concrete technique: turn locality‑sensitive hashing into an importance sampler so kernel‑sum estimation gets query time ~1/√μ (vs 1/μ for uniform… | ||
| Efficient Profile Maximum Likelihood for Universal Symmetric Property Estimation | Robust and High-Dimensional Statistics (Simons Institute workshop, 2018) | 2018-10-29 |
Algorithm computes an approximate profile maximum likelihood distribution with objective value within a factor exp(O(N^{2/3})) of optimal, running in… | ||
| Integrating Functions via Distance Sensitive Hashing | Real-Time Decision Making 2018 | 2018-04-30 |
Claims a data structure that estimates partition-like sums z(y)=sum_x exp(phi(<x,y>)) faster than naive sampling: random sampling needs ~1/mu probes but this… | ||
| Local Guarantees in Graph Cuts and Clustering | Discrete Optimization via Continuous Relaxation | 2017-09-11 |
Defines min-max variants of cuts and correlation clustering, gives an LP relaxation and a deterministic ball-growing rounding that picks a 1/7 ball then a 3/7… | ||
| Exact Recovery via Convex Relaxations | Spectral Algorithms: From Theory to Practice 2014 | 2014-10-27 |
Convex relaxations often recover exact clusterings under random models: experiments show a pairwise LP is integral 88% of the time, strengthened to 100% for… | ||
| Tensor Decompositions: Uniqueness and Smoothed Analysis | Semidefinite Optimization, Approximation and Applications 2014 | 2014-09-24 |
Proves a robust analog of Kruskal's theorem so noisy empirical moment tensors yield factor estimates with polynomially related error, and analyzes a smoothed… | ||
| nothing matches | ||