conftrace_

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)

A Higher-Order Kolmogorov-Smirnov Test AISTATS 2019
Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference AISTATS 2019
Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables AISTATS 2019
Credit Assignment Techniques in Stochastic Computation Graphs AISTATS 2019
Efficient Bayesian Optimization for Target Vector Estimation AISTATS 2019
Correspondence Analysis Using Neural Networks AISTATS 2019
Multi-Observation Regression AISTATS 2019
Adaptive MCMC via Combining Local Samplers AISTATS 2019
Variance reduction properties of the reparameterization trick AISTATS 2019
Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization AISTATS 2019
Variational Noise-Contrastive Estimation AISTATS 2019
Improving Quadrature for Constrained Integrands AISTATS 2019
High Dimensional Inference in Partially Linear Models AISTATS 2019
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era AISTATS 2019
A Unified Weight Learning Paradigm for Multi-view Learning AISTATS 2019
Region-Based Active Learning AISTATS 2019
Precision Matrix Estimation with Noisy and Missing Data AISTATS 2019
Exploring $k$ out of Top $ρ$ Fraction of Arms in Stochastic Bandits AISTATS 2019
AutoML from Service Provider’s Perspective: Multi-device, Multi-tenant Model Selection with GP-EI AISTATS 2019
On Theory for BART AISTATS 2019
On the Dynamics of Gradient Descent for Autoencoders AISTATS 2019
Complexities in Projection-Free Stochastic Non-convex Minimization AISTATS 2019
Efficient Greedy Coordinate Descent for Composite Problems AISTATS 2019
Decentralized Gradient Tracking for Continuous DR-Submodular Maximization AISTATS 2019
Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models AISTATS 2019