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Optimization

341 directly classified papers

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Papers

Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization NIPS 2020
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees AAAI 2020
Training and Inference Methods for High-Coverage Neural Machine Translation ACL 2020
Determinant Regularization for Gradient-Efficient Graph Matching CVPR 2020
Non-Adversarial Video Synthesis With Learned Priors CVPR 2020
A Spectral Method for Unsupervised Multi-Document Summarization EMNLP 2020
On the Noisy Gradient Descent that Generalizes as SGD ICML 2020
Optimizing Word Segmentation for Downstream Task EMNLP 2020
Controllable Orthogonalization in Training DNNs CVPR 2020
Protecting Geolocation Privacy of Photo Collections AAAI 2020
SPAN: A Stochastic Projected Approximate Newton Method AAAI 2020
Finding Most Compatible Phylogenetic Trees over Multi-State Characters AAAI 2020
Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems AAAI 2020
Bounded Incentives in Manipulating the Probabilistic Serial Rule AAAI 2020
Cakewalk Sampling AAAI 2020
Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent AAAI 2020
Diversity can be Transferred: Output Diversification for White- and Black-box Attacks NIPS 2020
Improved Algorithms for Convex-Concave Minimax Optimization NIPS 2020
Model Inversion Networks for Model-Based Optimization NIPS 2020
Interior Point Solving for LP-based prediction+optimisation NIPS 2020
Myersonian Regression NIPS 2020
Generalization Bound of Gradient Descent for Non-Convex Metric Learning NIPS 2020
Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining NIPS 2020
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training NIPS 2020
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method NIPS 2020