activity
20202026
most citedOnline Bipartite Matching with Advice: Tight Robustness-Consistency Tradeoffs for the Two-Stage Model

13 citations · 26 across the 10 of their papers we have counts for

collaborators

11 papers

cs.DS2026

Straightforward Entropy-Sensitive Mergesort

Bill Jin, Alex Zihan Xu

In this paper, we present a stable mergesort variant, "directional mergesort", that to sort an array of elements makes no more than comparisons and moves w…

math.OC2023

Sample Complexity Analysis for Adaptive Optimization Algorithms with Stochastic Oracles

Billy Jin, Katya Scheinberg, Miaolan Xie

Several classical adaptive optimization algorithms, such as line search and trust region methods, have been recently extended to stochastic settings where function values, gradient…

cs.DS2022

A 4/3-Approximation Algorithm for Half-Integral Cycle Cut Instances of the TSP

Billy Jin, Nathan Klein, David P. Williamson

A long-standing conjecture for the traveling salesman problem (TSP) states that the integrality gap of the standard linear programming relaxation of the TSP is at most 4/3. Despite…

cs.GT2022★ 1 cited

Proportionally Fair Online Allocation of Public Goods with Predictions

Siddhartha Banerjee, Vasilis Gkatzelis, Safwan Hossain +3

We design online algorithms for the fair allocation of public goods to a set of agents over a sequence of rounds and focus on improving their performance using predictions.…

cs.DM2022

The Two-Stripe Symmetric Circulant TSP is in P

Samuel C. Gutekunst, Billy Jin, David P. Williamson

The symmetric circulant TSP is a special case of the traveling salesman problem in which edge costs are symmetric and obey circulant symmetry. Despite the substantial symmetry of t…

cs.DS2022★ 13 cited

Online Bipartite Matching with Advice: Tight Robustness-Consistency Tradeoffs for the Two-Stage Model

Billy Jin, Will Ma

Two-stage bipartite matching is a fundamental problem of optimization under uncertainty introduced by Feng, Niazadeh, and Saberi (2021), who study it under the stochastic and adver…

cs.DS2021

Cut-Toggling and Cycle-Toggling for Electrical Flow and Other p-Norm Flows

Monika Henzinger, Billy Jin, Richard Peng +1

We study the problem of finding flows in undirected graphs so as to minimize the weighted -norm of the flow for any . When , the problem is that of finding an electr…

math.OC2021★ 2 cited

High Probability Complexity Bounds for Adaptive Step Search Based on Stochastic Oracles

Billy Jin, Katya Scheinberg, Miaolan Xie

We consider a step search method for continuous optimization under a stochastic setting where the function values and gradients are available only through inexact probabilistic zer…

cs.DS2020

A Combinatorial Cut-Toggling Algorithm for Solving Laplacian Linear Systems

Monika Henzinger, Billy Jin, Richard Peng +1

Over the last two decades, a significant line of work in theoretical algorithms has made progress in solving linear systems whose coefficient matrix is the Laplacian matrix of a we…

cs.GT2020★ 10 cited

Online Nash Social Welfare Maximization with Predictions

Siddhartha Banerjee, Vasilis Gkatzelis, Artur Gorokh +1

We consider the problem of allocating a set of divisible goods to agents in an online manner, aiming to maximize the Nash social welfare, a widely studied objective which provi…

cs.DS2020

Improved Analysis of RANKING for Online Vertex-Weighted Bipartite Matching in the Random Order Model

Billy Jin, David P. Williamson

In this paper, we consider the online vertex-weighted bipartite matching problem in the random arrival model. We consider the generalization of the RANKING algorithm for this probl…