16 citations · 38 across the 9 of their papers we have counts for
9 papers
Branch & Learn with Post-hoc Correction for Predict+Optimize with Unknown Parameters in Constraints
Xinyi Hu, Jasper C. H. Lee, Jimmy H. M. Lee
Combining machine learning and constrained optimization, Predict+Optimize tackles optimization problems containing parameters that are unknown at the time of solving. Prior works f…
Predict+Optimize for Packing and Covering LPs with Unknown Parameters in Constraints
Xinyi Hu, Jasper C. H. Lee, Jimmy H. M. Lee
Predict+Optimize is a recently proposed framework which combines machine learning and constrained optimization, tackling optimization problems that contain parameters that are unkn…
Augmenting Stream Constraint Programming with Eventuality Conditions
Jasper C. H. Lee, Jimmy H. M. Lee, Allen Z. Zhong
Stream constraint programming is a recent addition to the family of constraint programming frameworks, where variable domains are sets of infinite streams over finite alphabets. Pr…
Tractability and Decompositions of Global Cost Functions
David Allouche, Christian Bessiere, Patrice Boizumault +8
Enforcing local consistencies in cost function networks is performed by applying so-called Equivalent Preserving Transformations (EPTs) to the cost functions. As EPTs transform the…
Consistency Techniques for Flow-Based Projection-Safe Global Cost Functions in Weighted Constraint Satisfaction
J. H. M. Lee, Ka Lun Leung
Many combinatorial problems deal with preferences and violations, the goal of which is to find solutions with the minimum cost. Weighted constraint satisfaction is a framework for…
A Comparison of Lex Bounds for Multiset Variables in Constraint Programming
Yat-Chiu Law, Jimmy Ho-Man Lee, May Hiu-Chun Woo +1
Set and multiset variables in constraint programming have typically been represented using subset bounds. However, this is a weak representation that neglects potentially useful in…