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)

Learning to Route in Similarity Graphs ICML 2019
Efficient optimization of loops and limits with randomized telescoping sums ICML 2019
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces ICML 2019
Switching Linear Dynamics for Variational Bayes Filtering ICML 2019
Greedy Layerwise Learning Can Scale To ImageNet ICML 2019
Overcoming Multi-model Forgetting ICML 2019
Optimal Kronecker-Sum Approximation of Real Time Recurrent Learning ICML 2019
More Efficient Off-Policy Evaluation through Regularized Targeted Learning ICML 2019
A Kernel Perspective for Regularizing Deep Neural Networks ICML 2019
Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff ICML 2019
Correlated bandits or: How to minimize mean-squared error online ICML 2019
Online Variance Reduction with Mixtures ICML 2019
Unreproducible Research is Reproducible ICML 2019
Target Tracking for Contextual Bandits: Application to Demand Side Management ICML 2019
Deep Counterfactual Regret Minimization ICML 2019
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem ICML 2019
Adversarial examples from computational constraints ICML 2019
Self-similar Epochs: Value in arrangement ICML 2019
Learning Generative Models across Incomparable Spaces ICML 2019
Rates of Convergence for Sparse Variational Gaussian Process Regression ICML 2019
What is the Effect of Importance Weighting in Deep Learning? ICML 2019
A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent ICML 2019
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances ICML 2019
Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games ICML 2019
Automated Model Selection with Bayesian Quadrature ICML 2019