On the infinite horizon constrained switched LQR problem. - Maximilian Balandat; Wei Zhang 013; Alessandro Abate (CDC, 2010)

Interpolation in output-feedback tube-based robust MPC. - Maximilian Balandat (CDC/ECC, 2011)

On infinite horizon switched LQR problems with state and control constraints. - Maximilian Balandat; Wei Zhang 013; Alessandro Abate (Syst. Control. Lett., 2012)

A dynamic VCG mechanism for random allocation spaces. - Maximilian Balandat; Claire J. Tomlin (Allerton, 2013)

On efficiency in mean field differential games. - Maximilian Balandat; Claire J. Tomlin (ACC, 2013)

Contract design for frequency regulation by aggregations of commercial buildings. - Maximilian Balandat; Frauke Oldewurtel; Mo Chen 001; Claire J. Tomlin (Allerton, 2014)

A mean field equilibrium for a model of interbank lending. - Maximilian Balandat; Ilya Tkachev; Alessandro Abate; Claire J. Tomlin (ACC, 2015)

The Hedge Algorithm on a Continuum. - Walid Krichene; Maximilian Balandat; Claire J. Tomlin; Alexandre M. Bayen (ICML, 2015)

A Bayesian perspective on Residential Demand Response using smart meter data. - Datong Zhou; Maximilian Balandat; Claire J. Tomlin (Allerton, 2016)

Building model identification during regular operation - empirical results and challenges. - Qie Hu; Frauke Oldewurtel; Maximilian Balandat; Evangelos Vrettos; Datong Zhou; Claire J. Tomlin (ACC, 2016)

Residential demand response targeting using machine learning with observational data. - Datong Zhou; Maximilian Balandat; Claire J. Tomlin (CDC, 2016)

Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum Games. - Maximilian Balandat; Walid Krichene; Claire J. Tomlin; Alexandre M. Bayen (NIPS, 2016)

Minimizing Regret on Reflexive Banach Spaces and Learning Nash Equilibria in Continuous Zero-Sum Games. - Maximilian Balandat; Walid Krichene; Claire J. Tomlin; Alexandre M. Bayen (CoRR, 2016)

Eliciting private user information for residential demand response. - Datong P. Zhou; Maximilian Balandat; Munther A. Dahleh; Claire J. Tomlin (CDC, 2017)

Estimating Treatment Effects of a Residential Demand Response Program Using Non-experimental Data. - Datong Paul Zhou; Maximilian Balandat; Claire Jennifer Tomlin (ICDM Workshops, 2017)

Incentive Design in Human-in-the-Loop Cyber-Physical Systems: A Case Study on Demand Response in California. - Datong P. Zhou; Maximilian Balandat; Claire J. Tomlin (CoRR, 2017)

Estimation and Targeting of Residential Households for Hour-Ahead Demand Response Interventions - A Case Study in California. - Datong P. Zhou; Maximilian Balandat; Claire J. Tomlin (CCTA, 2018)

BoTorch: Programmable Bayesian Optimization in PyTorch. - Maximilian Balandat; Brian Karrer; Daniel R. Jiang; Samuel Daulton; Benjamin Letham; Andrew Gordon Wilson; Eytan Bakshy (CoRR, 2019)

Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees. - Shali Jiang 001; Daniel R. Jiang; Maximilian Balandat; Brian Karrer; Jacob R. Gardner; Roman Garnett (NeurIPS, 2020)

BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization. - Maximilian Balandat; Brian Karrer; Daniel R. Jiang; Samuel Daulton; Benjamin Letham; Andrew Gordon Wilson; Eytan Bakshy (NeurIPS, 2020)

Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization. - Samuel Daulton; Maximilian Balandat; Eytan Bakshy (NeurIPS, 2020)

Optimizing Coverage and Capacity in Cellular Networks using Machine Learning. - Ryan M. Dreifuerst; Samuel Daulton; Yuchen Qian; Paul Parayil Varkey; Maximilian Balandat; Sanjay Kasturia; Anoop Tomar; Ali Yazdan 001; Vish Ponnampalam; Robert W. Heath Jr. (ICASSP, 2021)

Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs. - Raul Astudillo; Daniel R. Jiang; Maximilian Balandat; Eytan Bakshy; Peter I. Frazier (NeurIPS, 2021)

Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement. - Samuel Daulton; Maximilian Balandat; Eytan Bakshy (NeurIPS, 2021)

Bayesian Optimization with High-Dimensional Outputs. - Wesley J. Maddox; Maximilian Balandat; Andrew Gordon Wilson; Eytan Bakshy (NeurIPS, 2021)

BOW: First Real-World Demonstration of a Firewall-based Bayesian Optimization System for Wavelength Deployment. - Zhizhen Zhong; Manya Ghobadi; Maximilian Balandat; Sanjeevkumar Katti; Abbas Kazerouni; Jonathan Leach; Mark McKillop; Ying Zhang 022 (OFC, 2021)

Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization. - David Eriksson; Pierce I-Jen Chuang; Samuel Daulton; Peng Xia; Akshat Shrivastava; Arun Babu; Shicong Zhao; Ahmed Aly; Ganesh Venkatesh; Maximilian Balandat (CoRR, 2021)

Sustainable AI: Environmental Implications, Challenges and Opportunities. - Carole-Jean Wu; Ramya Raghavendra; Udit Gupta; Bilge Acun; Newsha Ardalani; Kiwan Maeng; Gloria Chang; Fiona Aga Behram; James Huang; Charles Bai; Michael Gschwind; Anurag Gupta; et al. (CoRR, 2021)

Optimizing High-Dimensional Physics Simulations via Composite Bayesian Optimization. - Wesley J. Maddox; Qing Feng; Maximilian Balandat (CoRR, 2021)

Robust Multi-Objective Bayesian Optimization Under Input Noise. - Samuel Daulton; Sait Cakmak; Maximilian Balandat; Michael A. Osborne; Enlu Zhou; Eytan Bakshy (ICML, 2022)

Sustainable AI: Environmental Implications, Challenges and Opportunities. - Carole-Jean Wu; Ramya Raghavendra; Udit Gupta; Bilge Acun; Newsha Ardalani; Kiwan Maeng; Gloria Chang; Fiona Aga Behram; Jinshi Huang; Charles Bai; Michael Gschwind; Anurag Gupta; et al. (MLSys, 2022)

Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization. - Samuel Daulton; Xingchen Wan; David Eriksson; Maximilian Balandat; Michael A. Osborne; Eytan Bakshy (NeurIPS, 2022)

Multi-objective Bayesian optimization over high-dimensional search spaces. - Samuel Daulton; David Eriksson; Maximilian Balandat; Eytan Bakshy (UAI, 2022)

Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. - Aryan Deshwal; Sebastian Ament; Maximilian Balandat; Eytan Bakshy; Janardhan Rao Doppa; David Eriksson (AISTATS, 2023)

Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information. - Samuel Daulton; Maximilian Balandat; Eytan Bakshy (ICML, 2023)

Unexpected Improvements to Expected Improvement for Bayesian Optimization. - Sebastian Ament; Samuel Daulton; David Eriksson; Maximilian Balandat; Eytan Bakshy (NeurIPS, 2023)

HHVM Performance Optimization for Large Scale Web Services. - Yuhao Li; Abhishek Gupta; Alex Yang; Peinan Chen; Joey Pinto; Brian Karrer; Mayank Pundir; Maximilian Balandat; Arun Kejariwal; Benjamin C. Lee (ICPE, 2023)

Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers. - P. Rodriguez-Fernandez; N. T. Howard; A. Saltzman; S. Kantamneni; J. Candy; C. Holland; Maximilian Balandat; Sebastian Ament; A. E. White (CoRR, 2023)

Quasi-Monte Carlo Methods in Python. - Pamphile T. Roy; Art B. Owen; Maximilian Balandat; Matt Haberland (J. Open Source Softw., 2023)

Bayesian Optimization of Function Networks with Partial Evaluations. - Poompol Buathong; Jiayue Wan; Raul Astudillo; Samuel Daulton; Maximilian Balandat; Peter I. Frazier (ICML, 2024)

Joint Composite Latent Space Bayesian Optimization. - Natalie Maus; Zhiyuan (Jerry) Lin; Maximilian Balandat; Eytan Bakshy (ICML, 2024)

Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need. - Shangda Yang; Vitaly Zankin; Maximilian Balandat; Stefan Scherer; Kevin T. Carlberg; Neil Walton; Kody J. H. Law (ICML, 2024)

Robust Gaussian Processes via Relevance Pursuit. - Sebastian Ament; Elizabeth Santorella; David Eriksson; Ben Letham; Maximilian Balandat; Eytan Bakshy (NeurIPS, 2024)

Scaling Gaussian Processes for Learning Curve Prediction via Latent Kronecker Structure. - Jihao Andreas Lin; Sebastian Ament; Maximilian Balandat; Eytan Bakshy (CoRR, 2024)

Experimenting, Fast and Slow: Bayesian Optimization of Long-term Outcomes with Online Experiments. - Qing Feng; Samuel Daulton; Benjamin Letham; Maximilian Balandat; Eytan Bakshy (KDD (1), 2025)

Scalable Gaussian Processes with Latent Kronecker Structure. - Jihao Andreas Lin; Sebastian Ament; Maximilian Balandat; David Eriksson; José Miguel Hernández-Lobato; Eytan Bakshy (CoRR, 2025)