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)

Batch Normalized Deep Boltzmann Machines ACML 2018
Collaboratively Weighting Deep and Classic Representation via $l_2$ Regularization for Image Classification ACML 2018
Construction of Incoherent Dictionaries via Direct Babel Function Minimization ACML 2018
Optimization Algorithm Inspired Deep Neural Network Structure Design ACML 2018
Boosting Dynamic Programming with Neural Networks for Solving NP-hard Problems ACML 2018
An Empirical Evaluation of Sketched SVD and its Application to Leverage Score Ordering ACML 2018
The Geometry of Random Features AISTATS 2018
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians AISTATS 2018
An Analysis of Categorical Distributional Reinforcement Learning AISTATS 2018
Accelerated Stochastic Power Iteration AISTATS 2018
Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach AISTATS 2018
Fast Threshold Tests for Detecting Discrimination AISTATS 2018
Iterative Supervised Principal Components AISTATS 2018
Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means AISTATS 2018
Parallelised Bayesian Optimisation via Thompson Sampling AISTATS 2018
Post Selection Inference with Kernels AISTATS 2018
On how complexity affects the stability of a predictor AISTATS 2018
On Truly Block Eigensolvers via Riemannian Optimization AISTATS 2018
Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond AISTATS 2018
IHT dies hard: Provable accelerated Iterative Hard Thresholding AISTATS 2018
Finding Global Optima in Nonconvex Stochastic Semidefinite Optimization with Variance Reduction AISTATS 2018
Outlier Detection and Robust Estimation in Nonparametric Regression AISTATS 2018
Integral Transforms from Finite Data: An Application of Gaussian Process Regression to Fourier Analysis AISTATS 2018
AdaGeo: Adaptive Geometric Learning for Optimization and Sampling AISTATS 2018
Online Learning with Non-Convex Losses and Non-Stationary Regret AISTATS 2018