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)

Stochastic Spectral and Conjugate Descent Methods NIPS 2018
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization NIPS 2018
Removing the Feature Correlation Effect of Multiplicative Noise NIPS 2018
Solving Large Sequential Games with the Excessive Gap Technique NIPS 2018
Step Size Matters in Deep Learning NIPS 2018
A Reduction for Efficient LDA Topic Reconstruction NIPS 2018
Convex Elicitation of Continuous Properties NIPS 2018
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal NIPS 2018
Minimax Statistical Learning with Wasserstein distances NIPS 2018
Efficient Stochastic Gradient Hard Thresholding NIPS 2018
Tight Bounds for Collaborative PAC Learning via Multiplicative Weights NIPS 2018
(Probably) Concave Graph Matching NIPS 2018
Video Prediction via Selective Sampling NIPS 2018
Snap ML: A Hierarchical Framework for Machine Learning NIPS 2018
Parsimonious Bayesian deep networks NIPS 2018
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion NIPS 2018
Learning latent variable structured prediction models with Gaussian perturbations NIPS 2018
Differentially Private Change-Point Detection NIPS 2018
Proximal Graphical Event Models NIPS 2018
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames NIPS 2018
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels NIPS 2018
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing NIPS 2018
Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting NIPS 2018
Optimization over Continuous and Multi-dimensional Decisions with Observational Data NIPS 2018
Neural Architecture Search with Bayesian Optimisation and Optimal Transport NIPS 2018