35 citations · 70 across the 19 of their papers we have counts for
28 papers
Optimal Dimension-Free Sampling for Regularized Classification
Meysam Alishahi, Alexander Munteanu, Simon Omlor +1
We prove optimal sampling bounds achieving -relative error for a broad class of Lipschitz continuous classification loss functions under various regularization t…
TabKDE: Simple and Scalable Tabular Data Generation with Kernel Density Estimates
Meysam Alishahi, Yan Zheng, Junpeng Wang +2
Tabular data generation considers a large table with multiple columns -- each column comprised of numerical, categorical, or sometimes ordinal values. The goal is to produce new ro…
No Dimensional Sampling Coresets for Classification
Meysam Alishahi, Jeff M. Phillips
We refine and generalize what is known about coresets for classification problems via the sensitivity sampling framework. Such coresets seek the smallest possible subsets of input…
Linear Distance Metric Learning with Noisy Labels
Meysam Alishahi, Anna Little, Jeff M. Phillips
In linear distance metric learning, we are given data in one Euclidean metric space and the goal is to find an appropriate linear map to another Euclidean metric space which respec…
The Matching Ramsey Number of Hypergraphs, Revisited
Saeed Shaebani, Meysam Alishahi
Suppose that a hypergraph and an arbitrary nonempty (finite or infinite) set of available colors are given. Each color is associated with a frequency , whe…
Topological bounds for graph representations over any field
Meysam Alishahi, Frédéric Meunier
Haviv ({\em European Journal of Combinatorics}, 2019) has recently proved that some topological lower bounds on the chromatic number of graphs are also lower bounds on their orthog…