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Escaping Saddles with Stochastic Gradients
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Estimation of Markov Chain via Rank-Constrained Likelihood
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Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
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Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap
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Equivalence of Multicategory SVM and Simplex Cone SVM Fast Computations and Statistical Theory
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End-to-End Learning for the Deep Multivariate Probit Model
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Entropy-SGD optimizes the prior of a PAC-Bayes bound Generalization properties of Entropy-SGD and data-dependent priors
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End-to-end Active Object Tracking via Reinforcement Learning
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Efficient Neural Audio Synthesis
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Efficient Neural Architecture Search via Parameters Sharing
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Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
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Efficient Gradient-Free Variational Inference using Policy Search
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Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning
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Efficient and Consistent Adversarial Bipartite Matching
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Dynamical Isometry and a Mean Field Theory of RNNs Gating Enables Signal Propagation in Recurrent Neural Networks
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