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)

Provably Efficient Reinforcement Learning via Surprise Bound AISTATS 2023
Sampling From a Schrödinger Bridge AISTATS 2023
A Multi-Task Gaussian Process Model for Inferring Time-Varying Treatment Effects in Panel Data AISTATS 2023
Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models AISTATS 2023
Active Learning for Single Neuron Models with Lipschitz Non-Linearities AISTATS 2023
Exploration in Reward Machines with Low Regret AISTATS 2023
On Universal Portfolios with Continuous Side Information AISTATS 2023
The Lauritzen-Chen Likelihood For Graphical Models AISTATS 2023
Bayesian Strategy-Proof Facility Location via Robust Estimation AISTATS 2023
The communication cost of security and privacy in federated frequency estimation AISTATS 2023
Learning While Scheduling in Multi-Server Systems With Unknown Statistics: MaxWeight with Discounted UCB AISTATS 2023
Piecewise Stationary Bandits under Risk Criteria AISTATS 2023
Does Label Differential Privacy Prevent Label Inference Attacks? AISTATS 2023
Conjugate Gradient Method for Generative Adversarial Networks AISTATS 2023
Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling AISTATS 2023
Learning Sparse Graphon Mean Field Games AISTATS 2023
Oblivious near-optimal sampling for multidimensional signals with Fourier constraints AISTATS 2023
Isotropic Gaussian Processes on Finite Spaces of Graphs AISTATS 2023
A Unified Perspective on Regularization and Perturbation in Differentiable Subset Selection AISTATS 2023
Nyström Method for Accurate and Scalable Implicit Differentiation AISTATS 2023
Neural Discovery of Permutation Subgroups AISTATS 2023
Feasible Recourse Plan via Diverse Interpolation AISTATS 2023
A Statistical Learning Take on the Concordance Index for Survival Analysis AISTATS 2023
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent AISTATS 2023
On Generalization of Decentralized Learning with Separable Data AISTATS 2023