| Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference | Apr 7, 2021 | BIG-bench Machine LearningCausal Inference | CodeCode Available | 0 |
| Learning Description Logic Ontologies. Five Approaches. Where Do They Stand? | Apr 2, 2021 | BIG-bench Machine LearningInductive logic programming | —Unverified | 0 |
| Why is AI hard and Physics simple? | Mar 31, 2021 | BIG-bench Machine LearningLearning Theory | —Unverified | 0 |
| Understanding the role of importance weighting for deep learning | Mar 28, 2021 | Deep LearningLearning Theory | —Unverified | 0 |
| Leaky Nets: Recovering Embedded Neural Network Models and Inputs through Simple Power and Timing Side-Channels -- Attacks and Defenses | Mar 26, 2021 | Learning Theory | —Unverified | 0 |
| Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning | Mar 25, 2021 | Learning Theoryreinforcement-learning | —Unverified | 0 |
| On the Complexity of Learning Description Logic Ontologies | Mar 25, 2021 | Learning Theory | —Unverified | 0 |
| On the Impact of Applying Machine Learning in the Decision-Making of Self-Adaptive Systems | Mar 18, 2021 | BIG-bench Machine LearningDecision Making | —Unverified | 0 |
| A deep learning theory for neural networks grounded in physics | Mar 18, 2021 | Deep LearningLearning Theory | —Unverified | 0 |
| Constrained Learning with Non-Convex Losses | Mar 8, 2021 | Adversarial RobustnessFairness | —Unverified | 0 |
| Learning Prediction Intervals for Regression: Generalization and Calibration | Feb 26, 2021 | Learning TheoryPrediction | —Unverified | 0 |
| Consistent Sparse Deep Learning: Theory and Computation | Feb 25, 2021 | Deep LearningGeneralization Bounds | CodeCode Available | 0 |
| Theoretical Understandings of Product Embedding for E-commerce Machine Learning | Feb 24, 2021 | BIG-bench Machine LearningDimensionality Reduction | —Unverified | 0 |
| Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution | Feb 23, 2021 | Few-Shot LearningLearning Theory | CodeCode Available | 0 |
| Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension | Feb 22, 2021 | counterfactualLearning Theory | —Unverified | 0 |
| KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-Zero Training Loss | Feb 22, 2021 | Learning Theory | —Unverified | 0 |
| On the robustness of randomized classifiers to adversarial examples | Feb 22, 2021 | Learning Theory | —Unverified | 0 |
| Geostatistical Learning: Challenges and Opportunities | Feb 17, 2021 | Learning TheoryModel Selection | CodeCode Available | 0 |
| Double-descent curves in neural networks: a new perspective using Gaussian processes | Feb 14, 2021 | Gaussian ProcessesLearning Theory | —Unverified | 0 |
| Distribution Free Uncertainty for the Minimum Norm Solution of Over-parameterized Linear Regression | Feb 14, 2021 | Learning TheoryPrediction | —Unverified | 0 |
| Private learning implies quantum stability | Feb 14, 2021 | Learning TheoryPAC learning | —Unverified | 0 |
| Local and Global Uniform Convexity Conditions | Feb 9, 2021 | Learning Theory | —Unverified | 0 |
| On the Hardness of PAC-learning Stabilizer States with Noise | Feb 9, 2021 | Learning TheoryPAC learning | —Unverified | 0 |
| Effects of quantum resources on the statistical complexity of quantum circuits | Feb 5, 2021 | Learning Theory | —Unverified | 0 |
| Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels | Feb 5, 2021 | Federated LearningGeneralization Bounds | —Unverified | 0 |