We analyze union-find using potential functions motivated by continuous
...
Employing Large Language Models (LLMs) to address mathematical problems ...
We analyze the bit complexity of efficient algorithms for fundamental
op...
The ℓ_p-norm regression problem is a classic problem in optimization
wit...
The optimal transport (OT) problem or earth mover's distance has wide
ap...
We present a nearly-linear time algorithm for finding a minimum-cost flo...
We give an algorithm that computes exact maximum flows and minimum-cost ...
We make several advances broadly related to the maintenance of electrica...
We show that the sparsified block elimination algorithm for solving
undi...
In this paper, we prove that over finite fields modulo primes, solving
g...
The current complexity of regression is nearly linear in the complexity ...
We study the problem of finding flows in undirected graphs so as to mini...
Diffusion is a fundamental graph procedure and has been a basic building...
We give an algorithm for computing exact maximum flows on graphs with m
...
We study distributed algorithms built around edge contraction based vert...
We present an Õ(m+n^1.5)-time randomized algorithm for maximum
cardinali...
Co-occurrence statistics for sequential data are common and important da...
Can linear systems be solved faster than matrix multiplication? While th...
Graph compression or sparsification is a basic information-theoretic and...
Graph embeddings are a ubiquitous tool for machine learning tasks, such ...
We present a general framework of designing efficient dynamic approximat...
We investigate the problem of efficiently computing optimal transport (O...
We show the existence of O(f(c)k) sized vertex sparsifiers that preserve...
We consider the classical Minimum Balanced Cut problem: given a graph G,...
We study deterministic algorithms for computing graph cuts, with focus o...
We propose a simple and computationally efficient method for dense subgr...
In this paper we study the problem of dynamically maintaining graph
prop...
We prove a separation between offline and online algorithms for finger-b...
Linear regression in ℓ_p-norm is a canonical optimization problem that
a...
We present algorithms for solving a large class of flow and regression
p...
We study dynamic algorithms for maintaining spectral vertex
sparsifiers ...
We provide improved convergence rates for various non-smooth
optimizatio...
We give improved algorithms for the ℓ_p-regression problem, _xx_p such t...
We show how to solve directed Laplacian systems in nearly-linear time. G...
We show that every graph is spectrally similar to the union of a constan...
We develop a framework for graph sparsification and sketching, based on ...
We present an asymptotically faster algorithm for solving linear systems...
Motivated by the study of matrix elimination orderings in combinatorial
...
In this paper we consider the fully-dynamic All-Pairs Effective
Resistan...
Current flow closeness centrality (CFCC) has a better discriminating abi...
We study faster algorithms for producing the minimum degree ordering use...
We consider a fundamental algorithmic question in spectral graph theory:...
Motivated by a sampling problem basic to computational statistical infer...
We study theoretical runtime guarantees for a class of optimization prob...