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)

Influence Diagnostics under Self-concordance AISTATS 2023
Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness AISTATS 2023
Large deviations rates for stochastic gradient descent with strongly convex functions AISTATS 2023
Stochastic Optimization for Spectral Risk Measures AISTATS 2023
Improving Adaptive Conformal Prediction Using Self-Supervised Learning AISTATS 2023
Ideal Abstractions for Decision-Focused Learning AISTATS 2023
Probabilistic Querying of Continuous-Time Event Sequences AISTATS 2023
Semantic Strengthening of Neuro-Symbolic Learning AISTATS 2023
Fast Variational Estimation of Mutual Information for Implicit and Explicit Likelihood Models AISTATS 2023
A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem AISTATS 2023
DIET: Conditional independence testing with marginal dependence measures of residual information AISTATS 2023
Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain Adaptation AISTATS 2023
Actually Sparse Variational Gaussian Processes AISTATS 2023
Competing against Adaptive Strategies in Online Learning via Hints AISTATS 2023
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images AISTATS 2023
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier AISTATS 2023
Sample Complexity of Distinguishing Cause from Effect AISTATS 2023
Score-based Quickest Change Detection for Unnormalized Models AISTATS 2023
Dropout-Resilient Secure Multi-Party Collaborative Learning with Linear Communication Complexity AISTATS 2023
Federated Asymptotics: a model to compare federated learning algorithms AISTATS 2023
Conformalized Unconditional Quantile Regression AISTATS 2023
Wasserstein Distributional Learning via Majorization-Minimization AISTATS 2023
HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent AISTATS 2023
Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees AISTATS 2023
On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data AISTATS 2023