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Optimization

14,969 papers

Papers per year

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Papers

Meta-Descent for Online, Continual Prediction AAAI 2019
Gradient-Based Inference for Networks with Output Constraints AAAI 2019
Lifted Proximal Operator Machines AAAI 2019
Learning Adaptive Random Features AAAI 2019
Towards Automated Semi-Supervised Learning AAAI 2019
Learning Logistic Circuits AAAI 2019
Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee AAAI 2019
Trust Region Evolution Strategies AAAI 2019
A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI AAAI 2019
A Bandit Approach to Maximum Inner Product Search AAAI 2019
Complex Unitary Recurrent Neural Networks Using Scaled Cayley Transform AAAI 2019
Cost-Sensitive Learning to Rank AAAI 2019
Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting AAAI 2019
Subspace Selection via DR-Submodular Maximization on Lattices AAAI 2019
Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP AAAI 2019
Robust Optimization over Multiple Domains AAAI 2019
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence AAAI 2019
Regularized Evolution for Image Classifier Architecture Search AAAI 2019
Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms AAAI 2019
Coreset Stochastic Variance-Reduced Gradient with Application to Optimal Margin Distribution Machine AAAI 2019
A Non–Convex Optimization Approach to Correlation Clustering AAAI 2019
Natural Option Critic AAAI 2019
Bounding Uncertainty for Active Batch Selection AAAI 2019
HyperAdam: A Learnable Task-Adaptive Adam for Network Training AAAI 2019
Robustness Can Be Cheap: A Highly Efficient Approach to Discover Outliers under High Outlier Ratios AAAI 2019