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Optimization

14,207 papers

Papers per year

Papers

Differentiable Learning of Submodular Models NIPS 2017
How regularization affects the critical points in linear networks NIPS 2017
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization NIPS 2017
Online Learning with a Hint NIPS 2017
Online Learning of Optimal Bidding Strategy in Repeated Multi-Commodity Auctions NIPS 2017
Gradient Methods for Submodular Maximization NIPS 2017
Adaptive Accelerated Gradient Converging Method under H\"{o}lderian Error Bound Condition NIPS 2017
Population Matching Discrepancy and Applications in Deep Learning NIPS 2017
Sharpness, Restart and Acceleration NIPS 2017
Affine-Invariant Online Optimization and the Low-rank Experts Problem NIPS 2017
On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning NIPS 2017
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation NIPS 2017
Solving Most Systems of Random Quadratic Equations NIPS 2017
On Structured Prediction Theory with Calibrated Convex Surrogate Losses NIPS 2017
Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach NIPS 2017
Task-based End-to-end Model Learning in Stochastic Optimization NIPS 2017
Approximation and Convergence Properties of Generative Adversarial Learning NIPS 2017
The Numerics of GANs NIPS 2017
Partial Hard Thresholding: Towards A Principled Analysis of Support Recovery NIPS 2017
SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks NIPS 2017
Rigorous Dynamics and Consistent Estimation in Arbitrarily Conditioned Linear Systems NIPS 2017
Renyi Differential Privacy Mechanisms for Posterior Sampling NIPS 2017
Decoupling "when to update" from "how to update" NIPS 2017
Variance-based Regularization with Convex Objectives NIPS 2017
Gaussian Quadrature for Kernel Features NIPS 2017