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Found 8 papers, 4 papers with code
Maximum flow-based formulation for the optimal location of electric vehicle charging stations
In this work, our goal is to expand the infrastructure of EV charging stations, in order to provide a better quality of service in terms of user satisfaction (and availability of charging stations).
Penalties and Rewards for Fair Learning in Paired Kidney Exchange Programs
Rather, the key factor in increasing the number of transplants, decreasing waiting times and improving group fairness is the judicious assignment of a negative weight (penalty) to the small number of non-directed donors in the kidney exchange program.
Optimization of the location and design of urban green spaces
We present a two-stage fair facility location and design model, which serves as a template model to assist public decision-makers at the city-level for the planning of urban green spaces.
Curriculum learning for multilevel budgeted combinatorial problems
Our framework is based on a simple curriculum: if an agent knows how to estimate the value of instances with budgets up to $B$, then solving instances with budget $B+1$ can be done in polynomial time regardless of the direction of the optimization by checking the value of every possible afterstate.
Combinatorial Optimization
Multi-agent Reinforcement Learning
Segmentation and Optimal Region Selection of Physiological Signals using Deep Neural Networks and Combinatorial Optimization
Physiological signals, such as the electrocardiogram and the phonocardiogram are very often corrupted by noisy sources.
Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming
We introduce a mixed integer program (MIP) for assigning importance scores to each neuron in deep neural network architectures which is guided by the impact of their simultaneous pruning on the main learning task of the network.
Game theoretical analysis of Kidney Exchange Programs
Recently, this was formulated as a non-cooperative two-player game and the game solutions (equilibria) were characterized when the entities objective function is the number of their patients receiving a kidney.
Computer Science and Game Theory 91-XX, 05Cxx, 90-XX
When Nash Meets Stackelberg
This article introduces a class of $Nash$ games among $Stackelberg$ players ($NASPs$), namely, a class of simultaneous non-cooperative games where the players solve sequential Stackelberg games.
Computer Science and Game Theory Optimization and Control
