57 citations · 135 across the 19 of their papers we have counts for
20 papers
A Shrinkage Path Heuristic for Wasserstein Distributionally Robust Optimization
Lingjun Meng, Ryan Cory-Wright, Wolfram Wiesemann
Wasserstein distributionally robust optimization (DRO) is a versatile and widely adopted framework for decision-making under uncertainty, yet its standard deterministic reformulati…
msPCA: An R Package for Sparse PCA with Multiple Components
Ryan Cory-Wright, Jean Pauphilet
We present msPCA: an open-source R package for sparse principal component analysis with multiple components. It implements an alternating maximization algorithm to generate a set o…
Compact Lifted Relaxations for Low-Rank Optimization
Ryan Cory-Wright, Jean Pauphilet
We develop tractable convex relaxations for rank-constrained quadratic optimization problems over matrices, a setting for which tractable relaxations are typically onl…
Pricing Discrete and Nonlinear Markets With Semidefinite Relaxations
Cheng Guo, Lauren Henderson, Ryan Cory-Wright +1
Nonconvexities in markets with discrete decisions and nonlinear constraints make efficient pricing challenging, often necessitating subsidies. A prime example is the unit commitmen…
Bridging the Gap Between Scientific Laws Derived by AI Systems and Canonical Knowledge via Abductive Inference with AI-Noether
Karan Srivastava, Sanjeeb Dash, Ryan Cory-Wright +3
Advances in AI have shown great potential in contributing to the acceleration of scientific discovery. Symbolic regression can fit interpretable models to data, but these models ar…
The Need for Verification in AI-Driven Scientific Discovery
Cristina Cornelio, Takuya Ito, Ryan Cory-Wright +2
Artificial intelligence (AI) is transforming the practice of science. Machine learning and large language models (LLMs) can generate hypotheses at a scale and speed far exceeding t…
Stability Regularized Cross-Validation
Ryan Cory-Wright, Andrés Gómez
We revisit the problem of ensuring strong test set performance via cross-validation, and propose a nested k-fold cross-validation scheme that selects hyperparameters by minimizing…
Improved Approximation Algorithms for Orthogonally Constrained Problems Using Semidefinite Optimization
Ryan Cory-Wright, Jean Pauphilet
Building on the blueprint from Goemans and Williamson (1995) for the Max-Cut problem, we construct a polynomial-time approximation algorithm for orthogonally constrained quadratic…
Evolving Scientific Discovery by Unifying Data and Background Knowledge with AI Hilbert
Ryan Cory-Wright, Cristina Cornelio, Sanjeeb Dash +2
The discovery of scientific formulae that parsimoniously explain natural phenomena and align with existing background theory is a key goal in science. Historically, scientists have…
Efficient Cross-Validation for Sparse Linear Regression
Ryan Cory-Wright, Andrés Gómez
Given a high-dimensional covariate matrix and a response vector, ridge-regularized sparse linear regression selects a subset of features that explains the relationship between cova…
Disjunctive Branch-and-Bound for Certifiably Optimal Low-Rank Matrix Completion
Dimitris Bertsimas, Ryan Cory-Wright, Sean Lo +1
Low-rank matrix completion consists of computing a matrix of minimal complexity that recovers a given set of observations as accurately as possible. Unfortunately, existing methods…
A Stochastic Benders Decomposition Scheme for Large-Scale Stochastic Network Design
Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet +1
Network design problems involve constructing edges in a transportation or supply chain network to minimize construction and daily operational costs. We study a stochastic version w…
Sparse PCA With Multiple Components
Ryan Cory-Wright, Jean Pauphilet
Sparse Principal Component Analysis (sPCA) is a cardinal technique for obtaining combinations of features, or principal components (PCs), that explain the variance of high-dimensio…
Decarbonizing OCP
Dimitris Bertsimas, Ryan Cory-Wright, Vassilis Digalakis
We present our collaboration with the OCP Group, one of the world's largest producers of phosphate and phosphate-based products, to reduce OCP's carbon emissions significantly. We…
Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach
Dimitris Bertsimas, Ryan Cory-Wright, Nicholas A. G. Johnson
We study the Sparse Plus Low-Rank decomposition problem (SLR), which is the problem of decomposing a corrupted data matrix into a sparse matrix of perturbations plus a low-rank mat…
A new perspective on low-rank optimization
Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet
A key question in many low-rank problems throughout optimization, machine learning, and statistics is to characterize the convex hulls of simple low-rank sets and judiciously apply…
On Polyhedral and Second-Order Cone Decompositions of Semidefinite Optimization Problems
Dimitris Bertsimas, Ryan Cory-Wright
We study a cutting-plane method for semidefinite optimization problems (SDOs), and supply a proof of the method's convergence, under a boundedness assumption. By relating the metho…
A unified approach to mixed-integer optimization problems with logical constraints
Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet
We propose a unified framework to address a family of classical mixed-integer optimization problems with logically constrained decision variables, including network design, facilit…
A Scalable Algorithm For Sparse Portfolio Selection
Dimitris Bertsimas, Ryan Cory-Wright
The sparse portfolio selection problem is one of the most famous and frequently-studied problems in the optimization and financial economics literatures. In a universe of risky ass…
On stochastic auctions in risk-averse electricity markets with uncertain supply
Ryan Cory-Wright, Golbon Zakeri
This paper studies risk in a stochastic auction which facilitates the integration of renewable generation in electricity markets. We model market participants who are risk averse a…