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Found 10 papers, 7 papers with code
Differentiable Convex Optimization Layers
In this paper, we propose an approach to differentiating through disciplined convex programs, a subclass of convex optimization problems used by domain-specific languages (DSLs) for convex optimization.
Non-line-of-sight Imaging with Partial Occluders and Surface Normals
Imaging objects obscured by occluders is a significant challenge for many applications.
A Rewriting System for Convex Optimization Problems
We describe a modular rewriting system for translating optimization problems written in a domain-specific language to forms compatible with low-level solver interfaces.
Optimization and Control Mathematical Software
Reconstructing Transient Images From Single-Photon Sensors
Computer vision algorithms build on 2D images or 3D videos that capture dynamic events at the millisecond time scale.
Unrolled Optimization with Deep Priors
A broad class of problems at the core of computational imaging, sensing, and low-level computer vision reduces to the inverse problem of extracting latent images that follow a prior distribution, from measurements taken under a known physical image formation model.
Multi-Period Trading via Convex Optimization
The methods we describe in this paper can be thought of as good ways to exploit predictions, no matter how they are made.
Dirty Pixels: Towards End-to-End Image Processing and Perception
As such, conventional imaging involves processing the RAW sensor measurements in a sequential pipeline of steps, such as demosaicking, denoising, deblurring, tone-mapping and compression.
Disciplined Multi-Convex Programming
A multi-convex optimization problem is one in which the variables can be partitioned into sets over which the problem is convex when the other variables are fixed.
Optimization and Control
Convex Optimization With Abstract Linear Operators
We introduce a convex optimization modeling framework that transforms a convex optimization problem expressed in a form natural and convenient for the user into an equivalent cone program in a way that preserves fast linear transforms in the original problem.
Convex Optimization in Julia
This paper describes Convex, a convex optimization modeling framework in Julia.
