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)

On the Calibration of Probabilistic Classifier Sets AISTATS 2023
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise AISTATS 2023
Learning to Optimize with Stochastic Dominance Constraints AISTATS 2023
Second Order Path Variationals in Non-Stationary Online Learning AISTATS 2023
Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach AISTATS 2023
A Mini-Block Fisher Method for Deep Neural Networks AISTATS 2023
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network AISTATS 2023
Pricing against a Budget and ROI Constrained Buyer AISTATS 2023
Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining AISTATS 2023
Incentive-aware Contextual Pricing with Non-parametric Market Noise AISTATS 2023
Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems AISTATS 2023
Randomized geometric tools for anomaly detection in stock markets AISTATS 2023
ForestPrune: Compact Depth-Pruned Tree Ensembles AISTATS 2023
Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games AISTATS 2023
Multiple-policy High-confidence Policy Evaluation AISTATS 2023
Domain Adaptation under Missingness Shift AISTATS 2023
Reducing Discretization Error in the Frank-Wolfe Method AISTATS 2023
Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning AISTATS 2023
Factorial SDE for Multi-Output Gaussian Process Regression AISTATS 2023
Learning to Generalize Provably in Learning to Optimize AISTATS 2023
Theory and Algorithm for Batch Distribution Drift Problems AISTATS 2023
On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy Evaluation AISTATS 2023
Precision/Recall on Imbalanced Test Data AISTATS 2023
Iterative Teaching by Data Hallucination AISTATS 2023
Probabilities of Causation: Role of Observational Data AISTATS 2023