2 citations · 4 across the 17 of their papers we have counts for
3 papers · 1 filter
Learning Discrete Decisions for MIPs with Constraint-Aware Diffusion
Vincenzo Di Vito, Mehdi Taghizadeh, Deepjyoti Deka +2
This paper proposes a novel learning-based approach to approximately solve instances of mixed-integer optimization problems. These problems are computationally challenging, as they…
Optimization Proxies using Limited Labeled Data and Training Time -- A Semi-Supervised Bayesian Neural Network Approach
Parikshit Pareek, Abhijith Jayakumar, Kaarthik Sundar +2
Constrained optimization problems arise in various engineering systems such as inventory management and power grids. Standard deep neural network (DNN) based machine learning proxi…
Data-Efficient Strategies for Probabilistic Voltage Envelopes under Network Contingencies
Parikshit Pareek, Deepjyoti Deka, Sidhant Misra
This work presents an efficient data-driven method to construct probabilistic voltage envelopes (PVE) using power flow learning in grids with network contingencies. First, a networ…