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Optimization & Theory

36,874 papers (3 classified directly here)

Subtopics

Optimization (14,983) Bayesian Inference (5,566) Learning Theory (5,334) Theory (4,955) Statistical Learning (4,117) Neural Network Optimization (3,649) Stochastic Processes (2,667) Loss Functions (1,162) Distributed Learning (1,135) Stochastic Methods (1,118) Online Algorithms (806) Statistics (684) Information Theory (318) Generalization (220) Sparse Optimization (158) Sample Complexity (99) Game Theory (30) Robust Optimization (17) Optimal Transport (14) Approximation Algorithms (10) Distributed Optimization (8) Convex Optimization (8)

Papers per year

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Papers (including subtopics)

Collaborative Filtering with Graph Information: Consistency and Scalable Methods NIPS 2015
Discrete Rényi Classifiers NIPS 2015
Preconditioned Spectral Descent for Deep Learning NIPS 2015
Accelerated Mirror Descent in Continuous and Discrete Time NIPS 2015
Accelerated Proximal Gradient Methods for Nonconvex Programming NIPS 2015
Monotone k-Submodular Function Maximization with Size Constraints NIPS 2015
Spherical Random Features for Polynomial Kernels NIPS 2015
A Dual Augmented Block Minimization Framework for Learning with Limited Memory NIPS 2015
Decomposition Bounds for Marginal MAP NIPS 2015
The Brain Uses Reliability of Stimulus Information when Making Perceptual Decisions NIPS 2015
On the Pseudo-Dimension of Nearly Optimal Auctions NIPS 2015
Fast Second Order Stochastic Backpropagation for Variational Inference NIPS 2015
Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions NIPS 2015
Non-asymptotic Analysis of Compressive Fisher Discriminants in terms of the Effective Dimension ACML 2015
Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities ACML 2015
A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections ACML 2015
Consistency of structured output learning with missing labels ACML 2015
Maximum Margin Partial Label Learning ACML 2015
Robust Multivariate Regression with Grossly Corrupted Observations and Its Application to Personality Prediction ACML 2015
Proximal Average Approximated Incremental Gradient Method for Composite Penalty Regularized Empirical Risk Minimization ACML 2015
Streaming Variational Inference for Dirichlet Process Mixtures ACML 2015
Expectation Propagation for Rectified Linear Poisson Regression ACML 2015
Surrogate regret bounds for generalized classification performance metrics ACML 2015
Regularized Policy Gradients: Direct Variance Reduction in Policy Gradient Estimation ACML 2015
Similarity-based Contrastive Divergence Methods for Energy-based Deep Learning Models ACML 2015