Strategic classification made practical

S Levanon, N Rosenfeld - International Conference on …, 2021 - proceedings.mlr.press
Strategic classification regards the problem of learning in settings where users can
strategically modify their features to improve outcomes. This setting applies broadly, and has …

Learning convex optimization models

A Agrawal, S Barratt, S Boyd - IEEE/CAA Journal of Automatica …, 2021 - ieeexplore.ieee.org
A convex optimization model predicts an output from an input by solving a convex
optimization problem. The class of convex optimization models is large, and includes as …

Flexible differentiable optimization via model transformations

M Besançon, J Dias Garcia, B Legat… - INFORMS Journal on …, 2024 - pubsonline.informs.org
We introduce DiffOpt. jl, a Julia library to differentiate through the solution of optimization
problems with respect to arbitrary parameters present in the objective and/or constraints …

OpenRANet: Neuralized Spectrum Access by Joint Subcarrier and Power Allocation with Optimization-based Deep Learning

S Chen, CW Tan, X Zhai, HV Poor - arxiv preprint arxiv:2409.12964, 2024 - arxiv.org
The next-generation radio access network (RAN), known as Open RAN, is poised to feature
an AI-native interface for wireless cellular networks, including emerging satellite-terrestrial …

Single Qubit Multi-Party Transmission Using Universal Symmetric Quantum Cloning

E Pelofske - arxiv preprint arxiv:2310.04920, 2023 - arxiv.org
We consider the hypothetical quantum network case where Alice wishes to transmit one
qubit of information (specifically a pure quantum state) to $ M $ parties, where $ M $ is some …

Applications of convex optimization in naval engineering

A Ritari - 2024 - aaltodoc.aalto.fi
Convex optimization is a class of nonlinear optimization with many useful theoretical and
computational properties. The global optimum can be computed very efficiently, even for …