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Optimization

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Papers

Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines ICML 2018
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning ICML 2018
Stein Variational Gradient Descent Without Gradient ICML 2018
Fairness Without Demographics in Repeated Loss Minimization ICML 2018
Fast Bellman Updates for Robust MDPs ICML 2018
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks ICML 2018
Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs ICML 2018
Unbiased Objective Estimation in Predictive Optimization ICML 2018
Differentially Private Matrix Completion Revisited ICML 2018
Pathwise Derivatives Beyond the Reparameterization Trick ICML 2018
Kronecker Recurrent Units ICML 2018
Fast Decoding in Sequence Models Using Discrete Latent Variables ICML 2018
Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games ICML 2018
Not All Samples Are Created Equal: Deep Learning with Importance Sampling ICML 2018
Frank-Wolfe with Subsampling Oracle ICML 2018
Convergence guarantees for a class of non-convex and non-smooth optimization problems ICML 2018
Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework ICML 2018
Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice ICML 2018
Data-Dependent Stability of Stochastic Gradient Descent ICML 2018
Understanding the Loss Surface of Neural Networks for Binary Classification ICML 2018
Binary Partitions with Approximate Minimum Impurity ICML 2018
Canonical Tensor Decomposition for Knowledge Base Completion ICML 2018
Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global ICML 2018
An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks ICML 2018
The Well-Tempered Lasso ICML 2018