This paper introduces approximation-preserving coresets, which provide weaker guarantees than strong coresets but stronger guarantees than weak coresets for preserving the costs of good solutions in b…

This paper establishes a connection between neural network approximation of score functions and approximation of probability distributions generated by reverse diffusion models.

This paper studies approximation algorithms for minimizing power losses in electrical distribution networks, proving hardness results and providing approximations for various configurations.

This paper presents a randomized algorithm that runs in $ ilde{O}(n^2)$ time and, with high probability, guarantees a 2-approximation for all pairs at distance at least $c$ in an undirected, unweighte…

This paper constructs an epsilon-cover of the joint value set of m constant-degree polynomials over a convex set H in the linfty-norm, with size n^(O(log(mn)/ε^2)), given that the polynomials have a c…

This paper presents approximation algorithms for the one-way directed Reachability-Preserving Minimum Edge Cut problem in directed graphs.

This paper improves the foundations of neural likelihood approximation for Bayesian inverse problems by making the learning problem strictly convex and showing convergence to the true likelihood.

This paper proposes an approximation algorithm for the submodular joint replenishment problem with decomposable submodular ordering cost functions, achieving an O(k)-approximation.

This paper proves conditions for efficiently approximating expectations of certain functions with respect to standard Gaussian or symmetric exponential probability measures.

This paper analyzes the finite-time behavior of nonlinear two-time-scale stochastic approximation and identifies a sharp boundary for decoupling the $k^{-1}$ rate.

This paper presents a polynomial-time differentially private algorithm for releasing a synthetic graph that approximates cut sizes in an input graph with error bound.

This paper presents a local computation algorithm to approximate the top eigenvector of a symmetric matrix with entries between -1 and 1, building on Swartworth and Woodruff's work.

This paper proves several properties about Extended Frege proof systems and circuit equivalence.

A new method for selecting knots in Generalized Additive Models using an extension of adaptive splines and a customized Fellner-Schall scheme.