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)

Fast and Robust Shortest Paths on Manifolds Learned from Data AISTATS 2019
Learning One-hidden-layer ReLU Networks via Gradient Descent AISTATS 2019
Gain estimation of linear dynamical systems using Thompson Sampling AISTATS 2019
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit AISTATS 2019
Stochastic algorithms with descent guarantees for ICA AISTATS 2019
Sample Complexity of Sinkhorn Divergences AISTATS 2019
Adaptive Gaussian Copula ABC AISTATS 2019
Top Feasible Arm Identification AISTATS 2019
Direct Acceleration of SAGA using Sampled Negative Momentum AISTATS 2019
Does data interpolation contradict statistical optimality? AISTATS 2019
A Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions AISTATS 2019
Differentially Private Online Submodular Minimization AISTATS 2019
Finding the bandit in a graph: Sequential search-and-stop AISTATS 2019
Statistical Learning under Nonstationary Mixing Processes AISTATS 2019
On Structure Priors for Learning Bayesian Networks AISTATS 2019
Truncated Back-propagation for Bilevel Optimization AISTATS 2019
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data AISTATS 2019
Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution AISTATS 2019
Lifted Weight Learning of Markov Logic Networks Revisited AISTATS 2019
Causal Discovery in the Presence of Missing Data AISTATS 2019
Learning Tree Structures from Noisy Data AISTATS 2019
Negative Momentum for Improved Game Dynamics AISTATS 2019
Data-dependent compression of random features for large-scale kernel approximation AISTATS 2019
The Gaussian Process Autoregressive Regression Model (GPAR) AISTATS 2019
Unsupervised Alignment of Embeddings with Wasserstein Procrustes AISTATS 2019