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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Generating Hard Random Boolean Formulas and Disjunctive Logic Programs IJCAI 2017 Generating High-Quality and Informative Conversation Responses with Sequence-to-Sequence Models EMNLP 2017 Generative Local Metric Learning for Kernel Regression NeurIPS 2017 Geometric Descent Method for Convex Composite Minimization NeurIPS 2017 Geometry of Neural Network Loss Surfaces via Random Matrix Theory ICML 2017 German in Flux: Detecting Metaphoric Change via Word Entropy CoNLL 2017 GibbsNet: Iterative Adversarial Inference for Deep Graphical Models NeurIPS 2017 Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs ICML 2017 Global Normalization of Convolutional Neural Networks for Joint Entity and Relation Classification EMNLP 2017 Global Optimality in Neural Network Training CVPR 2017 Global optimization of Lipschitz functions ICML 2017 Global SNR Estimation of Speech Signals for Unknown Noise Conditions Using Noise Adapted Non-Linear Regression Interspeech 2017 Glottal Model Based Speech Beamforming for ad-hoc Microphone Arrays Interspeech 2017 GPflow: A Gaussian Process Library using TensorFlow JMLR 2017 Gradient Boosted Decision Trees for High Dimensional Sparse Output ICML 2017 Gradient Boosting on Stochastic Data Streams AISTATS 2017 Gradient Coding: Avoiding Stragglers in Distributed Learning ICML 2017 Gradient Descent Can Take Exponential Time to Escape Saddle Points NeurIPS 2017 Gradient descent GAN optimization is locally stable NeurIPS 2017 Gradient Methods for Submodular Maximization NeurIPS 2017 Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares ICML 2017 Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling ICML 2017 Graph Matching via Multiplicative Update Algorithm NeurIPS 2017 Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees NeurIPS 2017 Group Sparse Optimization via lp,q Regularization JMLR 2017