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)

Neural Simulated Annealing AISTATS 2023
Adaptation to Misspecified Kernel Regularity in Kernelised Bandits AISTATS 2023
Gaussian Processes on Distributions based on Regularized Optimal Transport AISTATS 2023
Optimal Contextual Bandits with Knapsacks under Realizability via Regression Oracles AISTATS 2023
Bounding Evidence and Estimating Log-Likelihood in VAE AISTATS 2023
Privacy-preserving Sparse Generalized Eigenvalue Problem AISTATS 2023
A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization AISTATS 2023
Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery AISTATS 2023
Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics AISTATS 2023
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms AISTATS 2023
Smoothly Giving up: Robustness for Simple Models AISTATS 2023
A Tighter Problem-Dependent Regret Bound for Risk-Sensitive Reinforcement Learning AISTATS 2023
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation AISTATS 2023
Is interpolation benign for random forest regression? AISTATS 2023
Faithful Heteroscedastic Regression with Neural Networks AISTATS 2023
Boosted Off-Policy Learning AISTATS 2023
A Contrastive Approach to Online Change Point Detection AISTATS 2023
Private Non-Convex Federated Learning Without a Trusted Server AISTATS 2023
Variational Boosted Soft Trees AISTATS 2023
Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions AISTATS 2023
Stochastic Mirror Descent for Large-Scale Sparse Recovery AISTATS 2023
High Probability Bounds for Stochastic Continuous Submodular Maximization AISTATS 2023
Average Adjusted Association: Efficient Estimation with High Dimensional Confounders AISTATS 2023
Reinforcement Learning for Adaptive Mesh Refinement AISTATS 2023
Risk Bounds on Aleatoric Uncertainty Recovery AISTATS 2023