Calvin Tsay - RankMe

61 papers A* 7A 1B 1Journal 49Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A survey and tutorial of reinforcement learning methods in Process Systems Engineering. Comput. Chem. Eng. Maximilian Bloor, Max Mowbray, Ehecatl Antonio del Rio-Chanona, Calvin Tsay
2026	J	`jnl`	Exact Certification of Data-Poisoning Attacks Using Mixed-Integer Programming. CoRR Philip Sosnin, Jodie Knapp, Fraser Kennedy, Josh Collyer, Calvin Tsay
2026	J	`jnl`	PC-Gym: Benchmark environments for process control problems. Comput. Chem. Eng. Maximilian Bloor, José Torraca, Ilya Orson Sandoval, Akhil Ahmed, Martha White, Mehmet Mercangöz, Calvin Tsay, Ehecatl Antonio del Rio-Chanona, Max Mowbray
2025	J	`jnl`	A quantile neural network framework for two-stage stochastic optimization. Expert Syst. Appl. Antonio Alcántara, Carlos Ruiz, Calvin Tsay
2025	J	`jnl`	Abstract Gradient Training: A Unified Certification Framework for Data Poisoning, Unlearning, and Differential Privacy. CoRR Philip Sosnin, Matthew Wicker, Josh Collyer, Calvin Tsay
2025	A*	`conf`	Certification for Differentially Private Prediction in Gradient-Based Training. ICML Matthew Wicker, Philip Sosnin, Igor Shilov, Adrianna Janik, Mark Niklas Müller, Yves-Alexandre de Montjoye, Adrian Weller, Calvin Tsay
2025	J	`jnl`	Certified Robustness to Data Poisoning in Gradient-Based Training. Trans. Mach. Learn. Res. Philip Sosnin, Mark Niklas Müller, Maximilian Baader, Calvin Tsay, Matthew Wicker
2025	A*	`conf`	EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization. ICML Mujin Cheon, Jay H. Lee, Dong-Yeun Koh, Calvin Tsay
2025	A	`conf`	Global Optimization of Gaussian Process Acquisition Functions Using a Piecewise-Linear Kernel Approximation. AISTATS Yilin Xie, Shiqiang Zhang, Joel A. Paulson, Calvin Tsay
2025	J	`jnl`	Global optimization of graph acquisition functions for neural architecture search. CoRR Yilin Xie, Shiqiang Zhang, Jixiang Qing, Ruth Misener, Calvin Tsay
2025	J	`jnl`	Hierarchical RL-MPC for Demand Response Scheduling. CoRR Maximilian Bloor, Ehecatl Antonio del Rio-Chanona, Calvin Tsay
2025	J	`jnl`	Provably Safe Model Updates. CoRR Leo Elmecker-Plakolm, Pierre Fasterling, Philip Sosnin, Calvin Tsay, Matthew Wicker
2025	J	`jnl`	Risk-constrained stochastic scheduling of multi-market energy storage systems. CoRR Gabriel D. Patrón, Di Zhang, Lavinia M. P. Ghilardi, Evelin Blom, Maldon Goodridge, Erik Solis, Hamidreza Jahangir, Jorge Angarita, Nandhini Ganesan, Kevin West, Nilay Shah, Calvin Tsay
2025	J	`jnl`	Survey and Tutorial of Reinforcement Learning Methods in Process Systems Engineering. CoRR Maximilian Bloor, Max Mowbray, Ehecatl Antonio del Rio-Chanona, Calvin Tsay
2025	J	`jnl`	System-Aware Neural ODE Processes for Few-Shot Bayesian Optimization. Trans. Mach. Learn. Res. Jixiang Qing, Rebecca D. Langdon, Robert M. Lee, Behrang Shafei, Mark van der Wilk, Calvin Tsay, Ruth Misener
2025	J	`jnl`	The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning. CoRR Toby Boyne, Juan S. Campos, Becky D. Langdon, Jixiang Qing, Yilin Xie, Shiqiang Zhang, Calvin Tsay, Ruth Misener, Daniel W. Davies, Kim E. Jelfs, Sarah Boyall, Thomas M. Dixon, Linden Schrecker, Jose Pablo Folch
2025	J	`jnl`	Training Neural ODEs Using Fully Discretized Simultaneous Optimization. CoRR Mariia Shapovalova, Calvin Tsay
2024	J	`jnl`	Bayesian optimization as a flexible and efficient design framework for sustainable process systems. CoRR Joel A. Paulson, Calvin Tsay
2024	J	`jnl`	Certificates of Differential Privacy and Unlearning for Gradient-Based Training. CoRR Matthew Wicker, Philip Sosnin, Adrianna Janik, Mark Niklas Müller, Adrian Weller, Calvin Tsay
2024	J	`jnl`	Certified Robustness to Data Poisoning in Gradient-Based Training. CoRR Philip Sosnin, Mark Niklas Müller, Maximilian Baader, Calvin Tsay, Matthew Wicker
2024	J	`jnl`	Constrained continuous-action reinforcement learning for supply chain inventory management. Comput. Chem. Eng. Radu Burtea, Calvin Tsay
2024	J	`jnl`	Control-Informed Reinforcement Learning for Chemical Processes. CoRR Maximilian Bloor, Akhil Ahmed, Niki Kotecha, Mehmet Mercangöz, Calvin Tsay, Ehecatl Antonio del Rio-Chanona
2024	J	`jnl`	EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization. CoRR Mujin Cheon, Jay H. Lee, Dong-Yeun Koh, Calvin Tsay
2024	J	`jnl`	Global Optimization of Gaussian Process Acquisition Functions Using a Piecewise-Linear Kernel Approximation. CoRR Yilin Xie, Shiqiang Zhang, Joel A. Paulson, Calvin Tsay
2024	J	`jnl`	Mixed-integer optimisation of graph neural networks for computer-aided molecular design. Comput. Chem. Eng. Tom McDonald, Calvin Tsay, Artur M. Schweidtmann, Neil Yorke-Smith
2024	J	`jnl`	PC-Gym: Benchmark Environments For Process Control Problems. CoRR Maximilian Bloor, José Torraca, Ilya Orson Sandoval, Akhil Ahmed, Martha White, Mehmet Mercangöz, Calvin Tsay, Ehecatl Antonio del Rio-Chanona, Max Mowbray
2024	—	`conf`	Scaling Mixed-Integer Programming for Certification of Neural Network Controllers Using Bounds Tightening. CDC Philip Sosnin, Calvin Tsay
2024	J	`jnl`	System-Aware Neural ODE Processes for Few-Shot Bayesian Optimization. CoRR Jixiang Qing, Becky D. Langdon, Robert M. Lee, Behrang Shafei, Mark van der Wilk, Calvin Tsay, Ruth Misener
2024	A*	`conf`	Transition Constrained Bayesian Optimization via Markov Decision Processes. NeurIPS Jose Pablo Folch, Calvin Tsay, Robert M. Lee, Behrang Shafei, Weronika Ormaniec, Andreas Krause, Mark van der Wilk, Ruth Misener, Mojmir Mutny
2024	J	`jnl`	Transition Constrained Bayesian Optimization via Markov Decision Processes. CoRR Jose Pablo Folch, Calvin Tsay, Robert M. Lee, Behrang Shafei, Weronika Ormaniec, Andreas Krause, Mark van der Wilk, Ruth Misener, Mojmír Mutný
2023	J	`jnl`	Combining multi-fidelity modelling and asynchronous batch Bayesian Optimization. Comput. Chem. Eng. Jose Pablo Folch, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
2023	J	`jnl`	Distributional constrained reinforcement learning for supply chain optimization. CoRR Jaime Sabal Bermúdez, Antonio del Rio-Chanona, Calvin Tsay
2023	J	`jnl`	Mixed-Integer Optimisation of Graph Neural Networks for Computer-Aided Molecular Design. CoRR Tom McDonald, Calvin Tsay, Artur M. Schweidtmann, Neil Yorke-Smith
2023	—	`conf`	Model-Based Feature Selection for Neural Networks: A Mixed-Integer Programming Approach. LION Shudian Zhao, Calvin Tsay, Jan Kronqvist
2023	J	`jnl`	Model-based feature selection for neural networks: A mixed-integer programming approach. CoRR Shudian Zhao, Calvin Tsay, Jan Kronqvist
2023	A*	`conf`	Optimizing over trained GNNs via symmetry breaking. NeurIPS Shiqiang Zhang, Juan S. Campos, Christian Feldmann, David Walz, Frederik Sandfort, Miriam Mathea, Calvin Tsay, Ruth Misener
2023	J	`jnl`	Practical Path-based Bayesian Optimization. CoRR Jose Pablo Folch, James Odgers, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
2023	J	`jnl`	When Deep Learning Meets Polyhedral Theory: A Survey. CoRR Joey Huchette, Gonzalo Muñoz, Thiago Serra, Calvin Tsay
2022	J	`jnl`	Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian Optimization. CoRR Jose Pablo Folch, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
2022	J	`jnl`	Maximizing information from chemical engineering data sets: Applications to machine learning. CoRR Alexander Thebelt, Johannes Wiebe, Jan Kronqvist, Calvin Tsay, Ruth Misener
2022	J	`jnl`	OMLT: Optimization & Machine Learning Toolkit. CoRR Francesco Ceccon, Jordan Jalving, Joshua Haddad, Alexander Thebelt, Calvin Tsay, Carl D. Laird, Ruth Misener
2022	J	`jnl`	OMLT: Optimization & Machine Learning Toolkit. J. Mach. Learn. Res. Francesco Ceccon, Jordan Jalving, Joshua Haddad, Alexander Thebelt, Calvin Tsay, Carl D. Laird, Ruth Misener
2022	J	`jnl`	P-split formulations: A class of intermediate formulations between big-M and convex hull for disjunctive constraints. CoRR Jan Kronqvist, Ruth Misener, Calvin Tsay
2022	A*	`conf`	SnAKe: Bayesian Optimization with Pathwise Exploration. NeurIPS Jose Pablo Folch, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
2022	J	`jnl`	SnAKe: Bayesian Optimization with Pathwise Exploration. CoRR Jose Pablo Folch, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
2022	A*	`conf`	Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces. NeurIPS Alexander Thebelt, Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Behrang Shafei, Ruth Misener
2022	J	`jnl`	Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces. CoRR Alexander Thebelt, Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Behrang Shafei, Ruth Misener
2021	B	`conf`	Between Steps: Intermediate Relaxations Between Big-M and Convex Hull Formulations. CPAIOR Jan Kronqvist, Ruth Misener, Calvin Tsay
2021	J	`jnl`	Between steps: Intermediate relaxations between big-M and convex hull formulations. CoRR Jan Kronqvist, Ruth Misener, Calvin Tsay
2021	J	`jnl`	Multi-Objective Constrained Optimization for Energy Applications via Tree Ensembles. CoRR Alexander Thebelt, Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Tom Tranter, Ruth Misener
2021	A*	`conf`	Partition-Based Formulations for Mixed-Integer Optimization of Trained ReLU Neural Networks. NeurIPS Calvin Tsay, Jan Kronqvist, Alexander Thebelt, Ruth Misener
2021	J	`jnl`	Partition-based formulations for mixed-integer optimization of trained ReLU neural networks. CoRR Calvin Tsay, Jan Kronqvist, Alexander Thebelt, Ruth Misener
2021	J	`jnl`	Sobolev trained neural network surrogate models for optimization. Comput. Chem. Eng. Calvin Tsay
2020	J	`jnl`	Identification and online updating of dynamic models for demand response of an industrial air separation unit. CoRR Calvin Tsay, Yanan Cao, Yajun Wang, Jesus Flores-Cerrillo, Michael Baldea
2019	—	`conf`	Automating Visual Inspection of Lyophilized Drug Products With Multi-Input Deep Neural Networks. CASE Calvin Tsay, Zheng Li
2019	J	`jnl`	Learning latent variable dynamic models for integrated production scheduling and control. CoRR Calvin Tsay, Michael Baldea
2019	J	`jnl`	Optimal demand response scheduling of an industrial air separation unit using data-driven dynamic models. Comput. Chem. Eng. Calvin Tsay, Ankur Kumar, Jesus Flores-Cerrillo, Michael Baldea
2018	J	`jnl`	A simulation-based optimization framework for integrating scheduling and model predictive control, and its application to air separation units. Comput. Chem. Eng. Lisia S. Dias, Richard C. Pattison, Calvin Tsay, Michael Baldea, Marianthi G. Ierapetritou
2018	J	`jnl`	A survey of optimal process design capabilities and practices in the chemical and petrochemical industries. Comput. Chem. Eng. Calvin Tsay, Richard C. Pattison, Michael R. Piana, Michael Baldea
2017	J	`jnl`	A superstructure-based design of experiments framework for simultaneous domain-restricted model identification and parameter estimation. Comput. Chem. Eng. Calvin Tsay, Richard C. Pattison, Michael Baldea, Ben G. Weinstein, Steven J. Hodson, Robert D. Johnson
2017	J	`jnl`	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. Richard C. Pattison, Calvin Tsay, Michael Baldea