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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)

Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA AISTATS 2016
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization AISTATS 2016
Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation AISTATS 2016
Graph Connectivity in Noisy Sparse Subspace Clustering AISTATS 2016
The Nonparametric Kernel Bayes Smoother AISTATS 2016
Universal Models of Multivariate Temporal Point Processes AISTATS 2016
Relationship between PreTraining and Maximum Likelihood Estimation in Deep Boltzmann Machines AISTATS 2016
Enumerating Equivalence Classes of Bayesian Networks using EC Graphs AISTATS 2016
NuC-MKL: A Convex Approach to Non Linear Multiple Kernel Learning AISTATS 2016
Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization AISTATS 2016
Batch Bayesian Optimization via Local Penalization AISTATS 2016
Fast and Scalable Structural SVM with Slack Rescaling AISTATS 2016
Variational Tempering AISTATS 2016
On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System AISTATS 2016
Scalable MCMC for Mixed Membership Stochastic Blockmodels AISTATS 2016
A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm AISTATS 2016
GLASSES: Relieving The Myopia Of Bayesian Optimisation AISTATS 2016
Stochastic Variational Inference for the HDP-HMM AISTATS 2016
Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016
Variational Gaussian Copula Inference AISTATS 2016
Accelerating Online Convex Optimization via Adaptive Prediction AISTATS 2016
Scalable geometric density estimation AISTATS 2016
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections AISTATS 2016
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models AISTATS 2016