Publications

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Sample-Efficient Bayesian Optimization with Transfer Learning for Heterogeneous Search Spaces. AutoML Conference (Workshop Track), 2024.

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Machine Learning Enabled Design and Optimization for 3D‐Printing of High‐Fidelity Presurgical Organ Models. Advanced Materials Technologies, 2024.

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Learning Surrogates for Offline Black-Box Optimization via Gradient Matching. Forty-first International Conference on Machine Learning (ICML), 2024.

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Streamflow Prediction with Uncertainty Quantification for Water Management. Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI), 2024.

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Offline Model-based Black-Box Optimization via Policy-guided Gradient Search. Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024.

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Multi-fidelity Bayesian Optimization of Covalent Organic Frameworks for Xenon/Krypton Separations. Digitial Discovery Journal, Royal Society of Chemistry, 2023.

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Gauche - A Library for Gaussian Processes in Chemistry. Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.

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Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. Twenty-Sixth International Conference on Artificial Intelligence and Statistics (AISTATS), 2023.

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Dynamic Power Management in Large Manycore Systems - A Learning-to-Search Framework. ACM Transactions on Design Automation of Electronic Systems (TODAES), 2023.

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Bayesian Optimization over Permutation Spaces. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), 2022.

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Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces. Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021.

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Bayesian Optimization of Nanoporous Materials. Molecular Systems Design and Engineering Journal, Royal Society of Chemistry, 2021.

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Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization. Journal of Artificial Intelligence Research (JAIR), 2021.

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Bayesian Optimization over Hybrid Spaces. Thirty-eighth International Conference on Machine Learning (ICML), 2021.

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Learning Pareto-Frontier Resource Management Policies for Heterogeneous SoCs - An Information-Theoretic Approach. Proceedings of 58th IEEE/ACM Design Automation Conference (DAC), 2021.

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High-Throughput Training of Deep CNNs on ReRAM-based Heterogeneous Architectures via Optimized Normalization Layers. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2021.

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Mercer Features for Efficient Combinatorial Bayesian Optimization. Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021.

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Scalable Combinatorial Bayesian Optimization with Tractable Statistical models. NeurIPS Workshop on Engineering Modeling, Simulation, and Design, 2020.

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Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints. NeurIPS Workshop on Machine Learning and the Physical Sciences, 2020.

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Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations. NeurIPS Workshop on Engineering Modeling, Simulation, and Design, 2020.

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Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization. AAAI Conference on Artificial Intelligence (AAAI), 2020.

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Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework. AAAI Conference on Artificial Intelligence (AAAI), 2020.

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Multi-Fidelity Multi-Objective Bayesian Optimization, An Output Space Entropy Search Approach. AAAI Conference on Artificial Intelligence (AAAI), 2020.

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Design of Multi-Output Switched-Capacitor Voltage Regulator via Machine Learning. 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2020.

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Design and Optimization of Energy-Accuracy Tradeoff Networks for Mobile Platforms via Pretrained Deep Models. ACM Transactions on Embedded Computing Systems (TECS), 2020.

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Max-value Entropy Search for Multi-Objective Bayesian Optimization. Advances in Neural Information Processing Systems (NeurIPS), 2019.

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MOOS: A multi-objective design space exploration and optimization framework for NoC enabled manycore systems. ACM Transactions on Embedded Computing Systems (TECS), 2019.

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Taming extreme heterogeneity via machine learning based design of autonomous manycore systems. Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis Companion (CODES/ISSS), 2019.

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Randomized greedy search for structured prediction: amortized inference and learning. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019.

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Learning and inference for structured prediction: a unifying perspective. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019.

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