46 citations · 46 across the 11 of their papers we have counts for
12 papers
Sequential Offering in On-Demand Platforms: On the Optimality of Greedy Ranking
Hongyao Ma, Will Ma, Matias Romero
On-demand platforms face the fundamental challenge of fulfilling time-sensitive jobs with independent workers who may decline offers. To minimize delays and unfulfilled jobs, platf…
Experimental Assortments for Choice Estimation and Nest Identification
Xintong Yu, Will Ma, Michael Zhao
What assortments (subsets of items) should be offered, to collect data for estimating a choice model over total items? We propose a structured, non-adaptive experiment design r…
AI Agents for Inventory Control: Human-LLM-OR Complementarity
Jackie Baek, Yaopeng Fu, Will Ma +1
Inventory control is a fundamental operations problem in which ordering decisions are traditionally guided by theoretically grounded operations research (OR) algorithms. However, s…
LLM-SAA: LLM-persona Generated Distributions for Decision-making
Jackie Baek, Yunhan Chen, Ziyu Chi +1
LLMs can generate a wealth of data, ranging from simulated personas imitating human valuations and preferences, to demand forecasts based on world knowledge. But how well do such L…
Personalized Promotions in Practice: Dynamic Allocation and Reference Effects
Jackie Baek, Will Ma, Dmitry Mitrofanov
Partnering with a large online retailer, we consider the problem of sending daily personalized promotions to a userbase of over 20 million customers. We propose an efficient policy…
Potential-Based Greedy Matching for Dynamic Delivery Pooling
Hongyao Ma, Will Ma, Matias Romero
We study the dynamic pooling of multiple orders into a single trip, a strategy widely adopted by online delivery platforms. When an order has to be dispatched, the platform must de…
Fair Secretaries with Unfair Predictions
Eric Balkanski, Will Ma, Andreas Maggiori
Algorithms with predictions is a recent framework for decision-making under uncertainty that leverages the power of machine-learned predictions without making any assumption about…
Survey of Data-driven Newsvendor: Unified Analysis and Spectrum of Achievable Regrets
Zhuoxin Chen, Will Ma
In the Newsvendor problem, the goal is to guess the number that will be drawn from some distribution, with asymmetric consequences for guessing too high vs. too low. In the data-dr…
Randomized Rounding Approaches to Online Allocation, Sequencing, and Matching
Will Ma
Randomized rounding is a technique that was originally used to approximate hard offline discrete optimization problems from a mathematical programming relaxation. Since then it has…
Sample Complexity of Posted Pricing for a Single Item
Billy Jin, Thomas Kesselheim, Will Ma +1
Selling a single item to self-interested buyers is a fundamental problem in economics, where the two objectives typically considered are welfare maximization and revenue maximi…
Optimizing Inventory Placement for a Downstream Online Matching Problem
Boris Epstein, Will Ma
We study the inventory placement problem of splitting units of a single item across warehouses in advance of a downstream online matching problem that represents the dynamic fu…
Benchmarking Reinforcement Learning Algorithms on Real-World Robots
A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan +2
Through many recent successes in simulation, model-free reinforcement learning has emerged as a promising approach to solving continuous control robotic tasks. The research communi…