5 citations · 5 across the 13 of their papers we have counts for
14 papers
Forecasting from Counterfactual Simulator Rollouts: A Sim2Real Evaluation
Angel Wang, Dominique Perrault-Joncas, Alvaro Maggiar +2
Deploying a new decision policy creates a cold-start problem for prediction models whose targets depend on the policy's actions: historical observations reflect earlier policies, w…
Proximal Residual Value Functions for Consistent Planning and Real-Time Execution
Harrison Waldon, Carson Eisenach, Akhil Bagaria +4
We study two-timescale decision systems in which a planning layer periodically supplies a continuation-value function to a real-time optimizer that allocates arriving resources, wi…
Towards Optimal Estimators for Randomized Control Trials
Harsh Parikh, Gabriel Levin-Konigsberg, Nilesh Tripuraneni +5
Randomized controlled trials (RCTs) are fundamental tools for causal inference across technology companies, pharmaceutical research, and federal agencies. While the standard differ…
Exploration and Experimentation with a Misspecified Simulator
Harsh Parikh, Gabriel Levin-Konigsberg, Dominique Perrault-Joncas +3
Randomized experiments are the standard for measuring causal effects that guide decisions, but are costly. Simulators calibrated to historical data offer a cheaper alternative, but…
Ready from Day 1: Population-Aware Coordination for Large-Scale Constrained Multi-Agent Systems
Angel Wang, Dominique Perrault-Joncas, Alvaro Maggiar +2
In large-scale multi-agent systems with shared resource constraints, an upstream planner must iteratively evaluate candidate resource plans -- assessing feasibility, aggregate resp…
TEA-Time: Transporting Effects Across Time
Harsh Parikh, Gabriel Levin-Konigsberg, Dominique Perrault-Joncas +1
Treatment effects estimated from a randomized controlled trial are local not only to the study population but also to the time at which the trial was conducted. The literature on g…
BRIDGE: Building Representations In Domain Guided Program Synthesis
Robert Joseph George, Carson Eisenach, Udaya Ghai +3
Large language models can generate plausible code, but remain brittle for formal verification in proof assistants such as Lean. A central scalability challenge is that verified syn…
Structure-Informed Deep Reinforcement Learning for Inventory Management
Alvaro Maggiar, Sohrab Andaz, Akhil Bagaria +4
This paper investigates the application of Deep Reinforcement Learning (DRL) to classical inventory management problems, with a focus on practical implementation considerations. We…
Marketplace Operators Can Induce Competitive Pricing
Tiffany Ding, Dominique Perrault-Joncas, Orit Ronen +4
As e-commerce marketplaces continue to grow in popularity, it has become increasingly important to understand the role and impact of marketplace operators on competition and social…
C2-DPO: Constrained Controlled Direct Preference Optimization
Kavosh Asadi, Julien Han, Idan Pipano +5
Direct preference optimization (\texttt{DPO}) has emerged as a promising approach for solving the alignment problem in AI. In this paper, we make two counter-intuitive observations…
A shared-revenue Bertrand game
Raj Pabari, Udaya Ghai, Dominique Perrault-Joncas +6
We introduce and analyze a variation of the Bertrand game in which the revenue is shared between two players. This game models situations in which one economic agent can provide go…
LLMForecaster: Improving Seasonal Event Forecasts with Unstructured Textual Data
Hanyu Zhang, Chuck Arvin, Dmitry Efimov +5
Modern time-series forecasting models often fail to make full use of rich unstructured information about the time series themselves. This lack of proper conditioning can lead to ob…
Meta-Analysis of Randomized Experiments with Applications to Heavy-Tailed Response Data
Nilesh Tripuraneni, Dhruv Madeka, Dean Foster +2
A central obstacle in the objective assessment of treatment effect (TE) estimators in randomized control trials (RCTs) is the lack of ground truth (or validation set) to test their…
Estimating Vector Fields on Manifolds and the Embedding of Directed Graphs
Dominique Perrault-Joncas, Marina Meila
This paper considers the problem of embedding directed graphs in Euclidean space while retaining directional information. We model a directed graph as a finite set of observations…