Taking the Human Out of the Loop: A Review of Bayesian Optimization von Shahriari, Bobak, Swersky, Kevin, Wang, Ziyu, Adams, Ryan P., de Freitas, Nando

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Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single von Vicol, Paul, Kolter, Zico, Swersky, Kevin

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Directly Fine-Tuning Diffusion Models on Differentiable Rewards von Clark, Kevin, Vicol, Paul, Swersky, Kevin, Fleet, David J

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Exploring and Benchmarking the Planning Capabilities of Large Language Models von Bohnet, Bernd, Nova, Azade, Parisi, Aaron T, Swersky, Kevin, Goshvadi, Katayoon, Dai, Hanjun, Schuurmans, Dale, Fiedel, Noah, Sedghi, Hanie

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Data-Driven Offline Optimization For Architecting Hardware Accelerators von Kumar, Aviral, Yazdanbakhsh, Amir, Hashemi, Milad, Swersky, Kevin, Levine, Sergey

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SentenceMIM: A Latent Variable Language Model von Livne, Micha, Swersky, Kevin, Fleet, David J

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MIM: Mutual Information Machine von Livne, Micha, Swersky, Kevin, Fleet, David J

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High Mutual Information in Representation Learning with Symmetric Variational Inference von Livne, Micha, Swersky, Kevin, Fleet, David J

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Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks von Mahdavi, Sadegh, Swersky, Kevin, Kipf, Thomas, Hashemi, Milad, Thrampoulidis, Christos, Liao, Renjie

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Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks von Yan, Yujun, Hashemi, Milad, Swersky, Kevin, Yang, Yaoqing, Koutra, Danai

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CUF: Continuous Upsampling Filters von Vasconcelos, Cristina, Oztireli, Cengiz, Matthews, Mark, Hashemi, Milad, Swersky, Kevin, Tagliasacchi, Andrea

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Human 3D keypoints via spatial uncertainty modeling von Williams, Francis, Litany, Or, Sud, Avneesh, Swersky, Kevin, Tagliasacchi, Andrea

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Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single von Vicol, Paul, Kolter, Zico, Swersky, Kevin

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Long-Span Question-Answering: Automatic Question Generation and QA-System Ranking via Side-by-Side Evaluation von Bohnet, Bernd, Swersky, Kevin, Liu, Rosanne, Awasthi, Pranjal, Nova, Azade, Snaider, Javier, Sedghi, Hanie, Parisi, Aaron T, Collins, Michael, Lazaridou, Angeliki, Firat, Orhan, Fiedel, Noah

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Learning to Improve Code Efficiency von Chen, Binghong, Tarlow, Daniel, Swersky, Kevin, Maas, Martin, Heiber, Pablo, Naik, Ashish, Hashemi, Milad, Ranganathan, Parthasarathy

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Learned Hardware/Software Co-Design of Neural Accelerators von Shi, Zhan, Sakhuja, Chirag, Hashemi, Milad, Swersky, Kevin, Lin, Calvin

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Directly Fine-Tuning Diffusion Models on Differentiable Rewards von Clark, Kevin, Vicol, Paul, Swersky, Kevin, Fleet, David J

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Multi-task recurrent neural networks von Swersky, Kevin Jordan, Hashemi, Milad Olia, Smith, Jamie Alexander

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Big Self-Supervised Models are Strong Semi-Supervised Learners von Chen, Ting, Kornblith, Simon, Swersky, Kevin, Norouzi, Mohammad, Hinton, Geoffrey

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Neural Execution Engines: Learning to Execute Subroutines von Yan, Yujun, Swersky, Kevin, Koutra, Danai, Ranganathan, Parthasarathy, Hashemi, Milad

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