Calvin Tsay

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 38

Top Topics

Markov Decision Process

Top Venues

Comput. Chem. Eng.

J. Mach. Learn. Res.

Publications

Jose Pablo Folch, Calvin Tsay, Robert M. Lee, Behrang Shafei, Weronika Ormaniec, Andreas Krause, Mark van der Wilk, Ruth Misener, Mojmír Mutný
Transition Constrained Bayesian Optimization via Markov Decision Processes. CoRR (2024)
Radu Burtea, Calvin Tsay
Constrained continuous-action reinforcement learning for supply chain inventory management. Comput. Chem. Eng. 181 (2024)
Joel A. Paulson, Calvin Tsay
Bayesian optimization as a flexible and efficient design framework for sustainable process systems. CoRR (2024)
Philip Sosnin, Mark Niklas Müller, Maximilian Baader, Calvin Tsay, Matthew Wicker
Certified Robustness to Data Poisoning in Gradient-Based Training. CoRR (2024)
Tom McDonald, Calvin Tsay, Artur M. Schweidtmann, Neil Yorke-Smith
Mixed-integer optimisation of graph neural networks for computer-aided molecular design. Comput. Chem. Eng. 185 (2024)
Jixiang Qing, Becky D. Langdon, Robert M. Lee, Behrang Shafei, Mark van der Wilk, Calvin Tsay, Ruth Misener
System-Aware Neural ODE Processes for Few-Shot Bayesian Optimization. CoRR (2024)
Matthew Wicker, Philip Sosnin, Adrianna Janik, Mark N. Müller, Adrian Weller, Calvin Tsay
Certificates of Differential Privacy and Unlearning for Gradient-Based Training. CoRR (2024)
Shiqiang Zhang, Juan S. Campos, Christian Feldmann, David Walz, Frederik Sandfort, Miriam Mathea, Calvin Tsay, Ruth Misener
Optimizing over trained GNNs via symmetry breaking. NeurIPS (2023)
Jaime Sabal Bermúdez, Antonio del Rio-Chanona, Calvin Tsay
Distributional constrained reinforcement learning for supply chain optimization. CoRR (2023)
Tom McDonald, Calvin Tsay, Artur M. Schweidtmann, Neil Yorke-Smith
Mixed-Integer Optimisation of Graph Neural Networks for Computer-Aided Molecular Design. CoRR (2023)
Shudian Zhao, Calvin Tsay, Jan Kronqvist
Model-based feature selection for neural networks: A mixed-integer programming approach. CoRR (2023)
Joey Huchette, Gonzalo Muñoz, Thiago Serra, Calvin Tsay
When Deep Learning Meets Polyhedral Theory: A Survey. CoRR (2023)
Shudian Zhao, Calvin Tsay, Jan Kronqvist
Model-Based Feature Selection for Neural Networks: A Mixed-Integer Programming Approach. LION (2023)
Jose Pablo Folch, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
Combining multi-fidelity modelling and asynchronous batch Bayesian Optimization. Comput. Chem. Eng. 172 (2023)
Jose Pablo Folch, James Odgers, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
Practical Path-based Bayesian Optimization. CoRR (2023)
Francesco Ceccon, Jordan Jalving, Joshua Haddad, Alexander Thebelt, Calvin Tsay, Carl D. Laird, Ruth Misener
OMLT: Optimization & Machine Learning Toolkit. CoRR (2022)
Jose Pablo Folch, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
SnAKe: Bayesian Optimization with Pathwise Exploration. CoRR (2022)
Jose Pablo Folch, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
SnAKe: Bayesian Optimization with Pathwise Exploration. NeurIPS (2022)
Francesco Ceccon, Jordan Jalving, Joshua Haddad, Alexander Thebelt, Calvin Tsay, Carl D. Laird, Ruth Misener
OMLT: Optimization & Machine Learning Toolkit. J. Mach. Learn. Res. 23 (2022)
Jose Pablo Folch, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian Optimization. CoRR (2022)
Alexander Thebelt, Johannes Wiebe, Jan Kronqvist, Calvin Tsay, Ruth Misener
Maximizing information from chemical engineering data sets: Applications to machine learning. CoRR (2022)
Alexander Thebelt, Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Behrang Shafei, Ruth Misener
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces. NeurIPS (2022)
Jan Kronqvist, Ruth Misener, Calvin Tsay
P-split formulations: A class of intermediate formulations between big-M and convex hull for disjunctive constraints. CoRR (2022)
Alexander Thebelt, Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Behrang Shafei, Ruth Misener
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces. CoRR (2022)
Alexander Thebelt, Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Tom Tranter, Ruth Misener
Multi-Objective Constrained Optimization for Energy Applications via Tree Ensembles. CoRR (2021)
Calvin Tsay
Sobolev trained neural network surrogate models for optimization. Comput. Chem. Eng. 153 (2021)
Jan Kronqvist, Ruth Misener, Calvin Tsay
Between Steps: Intermediate Relaxations Between Big-M and Convex Hull Formulations. CPAIOR (2021)
Calvin Tsay, Jan Kronqvist, Alexander Thebelt, Ruth Misener
Partition-based formulations for mixed-integer optimization of trained ReLU neural networks. CoRR (2021)
Jan Kronqvist, Ruth Misener, Calvin Tsay
Between steps: Intermediate relaxations between big-M and convex hull formulations. CoRR (2021)
Calvin Tsay, Jan Kronqvist, Alexander Thebelt, Ruth Misener
Partition-Based Formulations for Mixed-Integer Optimization of Trained ReLU Neural Networks. NeurIPS (2021)
Calvin Tsay, Yanan Cao, Yajun Wang, Jesus Flores-Cerrillo, Michael Baldea
Identification and online updating of dynamic models for demand response of an industrial air separation unit. CoRR (2020)
Calvin Tsay, Zheng Li
Automating Visual Inspection of Lyophilized Drug Products With Multi-Input Deep Neural Networks. CASE (2019)
Calvin Tsay, Michael Baldea
Learning latent variable dynamic models for integrated production scheduling and control. CoRR (2019)
Calvin Tsay, Ankur Kumar, Jesus Flores-Cerrillo, Michael Baldea
Optimal demand response scheduling of an industrial air separation unit using data-driven dynamic models. Comput. Chem. Eng. 126 (2019)
Calvin Tsay, Richard C. Pattison, Michael R. Piana, Michael Baldea
A survey of optimal process design capabilities and practices in the chemical and petrochemical industries. Comput. Chem. Eng. 112 (2018)
Lisia S. Dias, Richard C. Pattison, Calvin Tsay, Michael Baldea, Marianthi G. Ierapetritou
A simulation-based optimization framework for integrating scheduling and model predictive control, and its application to air separation units. Comput. Chem. Eng. 113 (2018)
Richard C. Pattison, Calvin Tsay, Michael Baldea
Pseudo-transient models for multiscale, multiresolution simulation and optimization of intensified reaction/separation/recycle processes: Framework and a dimethyl ether production case study. Comput. Chem. Eng. 105 (2017)
Calvin Tsay, Richard C. Pattison, Michael Baldea, Ben G. Weinstein, Steven J. Hodson, Robert D. Johnson
A superstructure-based design of experiments framework for simultaneous domain-restricted model identification and parameter estimation. Comput. Chem. Eng. 107 (2017)