118 citations · 152 across the 16 of their papers we have counts for
4 papers · 1 filter
Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization
James Kotary, Jacob Christopher, My H Dinh +1
The integration of constrained optimization models as components in deep networks has led to promising advances on many specialized learning tasks. A central challenge in this sett…
Predict-Then-Optimize by Proxy: Learning Joint Models of Prediction and Optimization
James Kotary, Vincenzo Di Vito, Jacob Christopher +2
Many real-world decision processes are modeled by optimization problems whose defining parameters are unknown and must be inferred from observable data. The Predict-Then-Optimize f…
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities
Jayanta Mandi, James Kotary, Senne Berden +4
Decision-focused learning (DFL) is an emerging paradigm that integrates machine learning (ML) and constrained optimization to enhance decision quality by training ML models in an e…
Backpropagation of Unrolled Solvers with Folded Optimization
James Kotary, My H. Dinh, Ferdinando Fioretto
The integration of constrained optimization models as components in deep networks has led to promising advances on many specialized learning tasks. A central challenge in this sett…