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- Stable Causal Estimation with Optimal Transport
- Near-Exponential Convergence Rates for kNN Classification based on Boltzmann Margin
- On the Last-Iterate Convergence of Clipped Gradient Methods
- Acceleration and its Limits in Gaussian Variational Inference
- Two-Stage Score Estimation for Group-Specific Diffusion Models
- Factor-Assisted Density Estimation: When Ambient Dimension Enables Oracle Rates
- Stochastic Gradient Descent: A Nonlinear Time Series Perspective
- Precise Asymptotics for Dense High-Dimensional Huber Regression under Heteroscedasticity
- A polylogarithmic bound for list replicability
- Multiscale Sequential Auditing of Quantile Regression with Point Masses
- LASER: Latent Space Adjoint Matching for Support-Constrained Entropy-Regularized Offline RL
- Nonconvex Composite Functional Constraints via First-Order Augmented Lagrangian Methods under Local Regularity
- Ranked Right, Sized Wrong: Ensemble Spread Fails Silently at Streamflow Extremes
- Estimating dynamic models by matching random features
- Dynamic models with p parameters are identified by 2p+1 random features
- On Complexity of Gaussian Sampling
- Testing Conditional Distribution Equality Using Generative Models
- Compound p-values for competition-based testing
- Posterior Frequencies and the Cost of Not Fitting: A Correction to a Memorization Lower Bound
- Fractional is Better: Learnable Derivative Orders in Neural Operator Learning
- Beyond Expert Rankings: Contrast Calibration for Mixed-Precision MoE Quantization
- From Plato to Aristotle: Toward a General Theory of Representation Hypotheses
- MAEM: Mitigating Recency Bias via a Replay-Free, Capacity-Controlled Dynamic Mixture of Experts for Class-Incremental Graph Learning
- The minimal width of neural networks and immersions of real projective space
- Mixed Poisson diffusion models and application to posterior sampling