| Convergence Rates for Learning Linear Operators from Noisy Data | Aug 27, 2021 | Learning Theory | —Unverified | 0 |
| Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications | Aug 24, 2021 | Adversarial RobustnessDeep Learning | —Unverified | 0 |
| Primal and Dual Combinatorial Dimensions | Aug 23, 2021 | Learning Theory | —Unverified | 0 |
| Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation | Aug 16, 2021 | BIG-bench Machine LearningLearning Theory | —Unverified | 0 |
| Empirical Risk Minimization for Time Series: Nonparametric Performance Bounds for Prediction | Aug 11, 2021 | Learning TheoryTime Series | —Unverified | 0 |
| Unified Regularity Measures for Sample-wise Learning and Generalization | Aug 9, 2021 | Learning TheoryMemorization | —Unverified | 0 |
| Path classification by stochastic linear recurrent neural networks | Aug 6, 2021 | ClassificationLearning Theory | —Unverified | 0 |
| Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information | Jul 28, 2021 | Learning Theory | —Unverified | 0 |
| Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling | Jul 24, 2021 | Autonomous DrivingLearning Theory | —Unverified | 0 |
| Towards Explaining Adversarial Examples Phenomenon in Artificial Neural Networks | Jul 22, 2021 | Learning Theory | —Unverified | 0 |
