The following pages link to Peter L. Bartlett (Q162843):
Displaying 28 items.
- The minimax distortion redundancy in empirical quantizer design (Q4701158) (← links)
- Structural risk minimization over data-dependent hierarchies (Q4701167) (← links)
- The importance of convexity in learning with squared loss (Q4701173) (← links)
- Valid Generalisation from Approximate Interpolation (Q4715266) (← links)
- 10.1162/153244303321897690 (Q4825353) (← links)
- A Regularization Approach to Metrical Task Systems (Q4930704) (← links)
- Neural Network Learning (Q4951814) (← links)
- Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems (Q4969058) (← links)
- (Q4998932) (← links)
- (Q5053192) (← links)
- Benign overfitting in linear regression (Q5073215) (← links)
- (Q5091718) (← links)
- Gradient Descent with Identity Initialization Efficiently Learns Positive-Definite Linear Transformations by Deep Residual Networks (Q5154121) (← links)
- (Q5159434) (← links)
- Information-Theoretic Lower Bounds on the Oracle Complexity of Stochastic Convex Optimization (Q5271983) (← links)
- (Q5381117) (← links)
- Bounded Parameter Markov Decision Processes with Average Reward Criterion (Q5434055) (← links)
- Multitask Learning with Expert Advice (Q5434070) (← links)
- Learning Theory (Q5473607) (← links)
- Convexity, Classification, and Risk Bounds (Q5754926) (← links)
- (Q5867280) (← links)
- Direct iterative tuning via spectral analysis (Q5926265) (← links)
- Model selection and error estimation (Q5959937) (← links)
- Comment (Q5965645) (← links)
- Corrigendum to: ``Prediction, learning, uniform convergence, and scale-sensitive dimensions'' (Q6142595) (← links)
- High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm (Q6324348) (← links)
- Bayesian Robustness: A Nonasymptotic Viewpoint (Q6567906) (← links)
- A diffusion process perspective on posterior contraction rates for parameters (Q6583523) (← links)
