7 citations · 8 across the 7 of their papers we have counts for
8 papers
The Curvature of Regret in Contextual Linear Optimization
Konstantinos Ziliaskopoulos, Alexander Vinel, Alice E. Smith
Decision-focused learning for linear optimization is complicated by the discontinuity of the optimizer, where small cost errors may leave the decision unchanged or move it to a dif…
Decision-Value Attribution in Predict-then-Optimize Systems
Konstantinos Ziliaskopoulos, Alexander Vinel, Alice E. Smith
Predictive models are increasingly embedded in operational decision-making, yet standard explanation methods typically explain forecasts rather than the decisions those forecasts i…
Efficient global estimation of conditional-value-at-risk through stochastic kriging and extreme value theory
Armin Khayyer, Alexander Vinel, Joseph J. Kennedy
We consider the problem of evaluating risk for a system that is modeled by a complex stochastic simulation with many possible input parameter values. Two sources of computational b…
Predictive machine learning for prescriptive applications: a coupled training-validating approach
Ebrahim Mortaz, Alexander Vinel
In this research we propose a new method for training predictive machine learning models for prescriptive applications. This approach, which we refer to as coupled validation, is b…
Benchmarking Graph Neural Networks on Link Prediction
Xing Wang, Alexander Vinel
In this paper, we benchmark several existing graph neural network (GNN) models on different datasets for link predictions. In particular, the graph convolutional network (GCN), Gra…
Reannealing of Decaying Exploration Based On Heuristic Measure in Deep Q-Network
Xing Wang, Alexander Vinel
Existing exploration strategies in reinforcement learning (RL) often either ignore the history or feedback of search, or are complicated to implement. There is also a very limited…