141 citations · 237 across the 46 of their papers we have counts for
10 papers · 1 filter
CoCoNet: Convex Conformal Network for Multi-Dimensional Uncertainty Regions
Alireza Moradi, Thomas Bruys, Pascal Van Hentenryck +1
Conformal prediction (CP) provides distribution-free coverage guarantees under exchangeability, but the efficiency of its prediction regions depends critically on the choice of the…
Match the Canvas, Not Just the Answer: Predictability-Aware SFT for Diffusion Language Models
Miao Li, Hanyang Jiang, Hengyu Fu +8
Diffusion language models (DLMs) enable flexible parallel generation by resolving tokens according to the model's evolving predictability rather than a fixed left-to-right order. T…
Distributed Linear Programming on GPU Clusters at Extreme Scale
Arnaud Deza, Santanu Dey, Pascal Van Hentenryck
Large linear programs can exceed the memory of a single compute node. Although first-order methods replace sparse factorizations with GPU-suited matrix-vector products, other solve…
End-to-End Supply Chain Planning in the Paper Industry Via Column Generation and Benders Decomposition
Changkun Guan, Amira Hijazi, Pascal Van Hentenryck
Problem definition: The paper studies an integrated end-to-end planning problem in large-scale paper manufacturing, where production scheduling, trimming decisions, vehicle loading…
Fusing Backdoors, Machine Learning, and Optimization for Large-Scale Parametric Mixed-Integer Programs
El Mehdi Er Raqabi, Pascal Van Hentenryck
Large-scale optimization problems are often solved repeatedly under similar structural conditions, leading to substantial computational overhead. This occurs in applications such a…
The Proxy Benders Decomposition
Changkun Guan, El Mehdi Er Raqabi, Mathieu Tanneau +1
Benders decomposition is a fundamental framework for solving large-scale mixed-integer optimization problems with complicating variables that, when fixed, yield significantly easie…
Decision-Focused On-Policy Learning for Contextual Linear Optimization with Partial Feedback
Wyame Benslimane, Tinghan Ye, Pascal Van Hentenryck +1
Decision-focused learning (DFL) trains predictive models by optimizing downstream decision quality rather than standalone prediction accuracy. For contextual linear optimization, m…
Democratizing Large-Scale Re-Optimization with LLM-Guided Model Patches
Tinghan Ye, Arnaud Deza, Ved Mohan +2
Optimization models developed by operations research (OR) experts are often deployed as decision-support systems in industrial settings. However, real-world environments are dynami…
A Hybrid Decomposition Approach for Stochastic Unit Commitment with Combined-Cycle Generators
Rosemary Barrass, Harsha Nagarajan, Mathieu Tanneau +2
The U.S. power grid is undergoing a paradigm shift as energy demand grows in scale and volatility. In response to this growing need, the U.S. has increased adoption of combined-cyc…
Plan, Verify and Fill: A Structured Parallel Decoding Approach for Diffusion Language Models
Miao Li, Hanyang Jiang, Sikai Cheng +6
Diffusion Language Models (DLMs) present a promising non-sequential paradigm for text generation, distinct from standard autoregressive (AR) approaches. However, current decoding s…