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Discovering and Exploiting Additive Structure for Bayesian Optimization.

, , , , и . AISTATS, том 54 из Proceedings of Machine Learning Research, стр. 1311-1319. PMLR, (2017)

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Roger B Edrington

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Unsupervised learning of hierarchical representations with convolutional deep belief networks., , , и . Commun. ACM, 54 (10): 95-103 (2011)Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions., , , , и . ICLR (Poster), OpenReview.net, (2019)Aggregated Momentum: Stability Through Passive Damping., , , и . ICLR (Poster), OpenReview.net, (2019)On the Quantitative Analysis of Decoder-Based Generative Models., , , и . ICLR (Poster), OpenReview.net, (2017)Distributed Second-Order Optimization using Kronecker-Factored Approximations., , и . ICLR (Poster), OpenReview.net, (2017)Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse., , , и . NeurIPS, стр. 9403-9413. (2019)Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?, , и . AISTATS, том 130 из Proceedings of Machine Learning Research, стр. 2476-2484. PMLR, (2021)Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition., , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 9955-9965. PMLR, (2021)Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians., и . NeurIPS, (2020)Evaluating Lossy Compression Rates of Deep Generative Models., , , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 4444-4454. PMLR, (2020)