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06/09/2023
Specifying and Solving Robust Empirical Risk Minimization Problems Using CVXPY
We consider robust empirical risk minimization (ERM), where model parame...
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05/04/2023
Joint Graph Learning and Model Fitting in Laplacian Regularized Stratified Models
Laplacian regularized stratified models (LRSM) are models that utilize t...
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05/01/2023
Fast Path Planning Through Large Collections of Safe Boxes
We present a fast algorithm for the design of smooth paths (or trajector...
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01/31/2023
Disciplined Saddle Programming
We consider convex-concave saddle point problems, and more generally con...
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11/11/2022
Tractable Evaluation of Stein's Unbiased Risk Estimator with Convex Regularizers
Stein's unbiased risk estimate (SURE) gives an unbiased estimate of the ...
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02/15/2022
A Light-Weight Multi-Objective Asynchronous Hyper-Parameter Optimizer
We describe a light-weight yet performant system for hyper-parameter opt...
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10/22/2021
Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP
Resource allocation problems in many computer systems can be formulated ...
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05/04/2021
Operator Splitting for Adaptive Radiation Therapy with Nonlinear Health Dynamics
We present an optimization-based approach to radiation treatment plannin...
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04/01/2021
Allocation of Fungible Resources via a Fast, Scalable Price Discovery Method
We consider the problem of assigning or allocating resources to a set of...
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03/03/2021
Minimum-Distortion Embedding
We consider the vector embedding problem. We are given a finite set of i...
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01/29/2021
Covariance Prediction via Convex Optimization
We consider the problem of predicting the covariance of a zero mean Gaus...
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01/29/2021
Low Rank Forecasting
We consider the problem of forecasting multiple values of the future of ...
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11/07/2020
Confidence bands for a log-concave density
We present a new approach for inference about a log-concave distribution...
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10/22/2020
Sample Efficient Reinforcement Learning with REINFORCE
Policy gradient methods are among the most effective methods for large-s...
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06/07/2020
Learning Convex Optimization Models
A convex optimization model predicts an output from an input by solving ...
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05/18/2020
Optimal Representative Sample Weighting
We consider the problem of assigning weights to a set of samples or data...
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05/04/2020
Fitting Laplacian Regularized Stratified Gaussian Models
We consider the problem of jointly estimating multiple related zero-mean...
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03/05/2020
Convex Optimization Over Risk-Neutral Probabilities
We consider a collection of derivatives that depend on the price of an u...
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01/27/2020
Eigen-Stratified Models
Stratified models depend in an arbitrary way on a selected categorical f...
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12/19/2019
Learning Convex Optimization Control Policies
Many control policies used in various applications determine the input o...
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10/28/2019
Differentiable Convex Optimization Layers
Recent work has shown how to embed differentiable optimization problems ...
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10/27/2019
Minimizing a Sum of Clipped Convex Functions
We consider the problem of minimizing a sum of clipped convex functions;...
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10/15/2019
Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize
Variable metric proximal gradient (VM-PG) is a widely used class of conv...
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05/30/2019
A General Optimization Framework for Dynamic Time Warping
Dynamic time warping (DTW) is a method that inputs two time-domain signa...
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05/02/2019
Disciplined Quasiconvex Programming
We present a composition rule involving quasiconvex functions that gener...
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04/26/2019
A Distributed Method for Fitting Laplacian Regularized Stratified Models
Stratified models are models that depend in an arbitrary way on a set of...
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04/10/2019
Least Squares Auto-Tuning
Least squares is by far the simplest and most commonly applied computati...
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12/10/2018
Disciplined Geometric Programming
We introduce log-log convex programs, which are optimization problems wi...
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10/22/2018
Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace from Position Data
Models for predicting aircraft motion are an important component of mode...
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08/01/2018
Network Optimization for Unified Packet and Circuit Switched Networks
Internet traffic continues to grow unabatedly at a rapid rate, driven la...
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11/21/2017
CVXR: An R Package for Disciplined Convex Optimization
CVXR is an R package that provides an object-oriented modeling language ...
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09/13/2017
A Rewriting System for Convex Optimization Problems
We describe a modular rewriting system for translating optimization prob...
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01/23/2017
Dirty Pixels: Optimizing Image Classification Architectures for Raw Sensor Data
Real-world sensors suffer from noise, blur, and other imperfections that...
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09/21/2016
Saturating Splines and Feature Selection
We extend the adaptive regression spline model by incorporating saturati...
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06/02/2016
Convolutional Imputation of Matrix Networks
A matrix network is a family of matrices, where the relationship between...
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09/21/2015
SnapVX: A Network-Based Convex Optimization Solver
SnapVX is a high-performance Python solver for convex optimization probl...
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03/04/2015
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights
We derive a second-order ordinary differential equation (ODE) which is t...
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10/17/2014
Convex Optimization in Julia
This paper describes Convex, a convex optimization modeling framework in...
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10/01/2014
Generalized Low Rank Models
Principal components analysis (PCA) is a well-known technique for approx...
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03/08/2012