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)

An Optimization-based Algorithm for Non-stationary Kernel Bandits without Prior Knowledge AISTATS 2023
Multi-armed Bandit Experimental Design: Online Decision-making and Adaptive Inference AISTATS 2023
Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits AISTATS 2023
Byzantine-Robust Federated Learning with Optimal Statistical Rates AISTATS 2023
Online Learning for Traffic Routing under Unknown Preferences AISTATS 2023
No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution AISTATS 2023
Mode-constrained Model-based Reinforcement Learning via Gaussian Processes AISTATS 2023
The Lie-Group Bayesian Learning Rule AISTATS 2023
A Finite Sample Complexity Bound for Distributionally Robust Q-learning AISTATS 2023
Membership Inference Attacks against Synthetic Data through Overfitting Detection AISTATS 2023
Online Learning for Non-monotone DR-Submodular Maximization: From Full Information to Bandit Feedback AISTATS 2023
No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities AISTATS 2023
Noise-Aware Statistical Inference with Differentially Private Synthetic Data AISTATS 2023
ASkewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks AISTATS 2023
Transport Elliptical Slice Sampling AISTATS 2023
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition AISTATS 2023
MARS: Masked Automatic Ranks Selection in Tensor Decompositions AISTATS 2023
Sparse Bayesian optimization AISTATS 2023
On the bias of K-fold cross validation with stable learners AISTATS 2023
Sample Efficiency of Data Augmentation Consistency Regularization AISTATS 2023
ANACONDA: An Improved Dynamic Regret Algorithm for Adaptive Non-Stationary Dueling Bandits AISTATS 2023
Deep Joint Source-Channel Coding with Iterative Source Error Correction AISTATS 2023
On-Demand Communication for Asynchronous Multi-Agent Bandits AISTATS 2023
The ELBO of Variational Autoencoders Converges to a Sum of Entropies AISTATS 2023
Autoencoded sparse Bayesian in-IRT factorization, calibration, and amortized inference for the Work Disability Functional Assessment Battery AISTATS 2023