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738 results on '"Nicolás, P"'

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1. Sharpness-Aware Minimization: General Analysis and Improved Rates

2. Re-evaluating Open-ended Evaluation of Large Language Models

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3. Symmetric observations without symmetric causal explanations

4. An Efficient Permutation-Based Kernel Two-Sample Test

5. The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks

6. Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods

7. Denoising Score Matching with Random Features: Insights on Diffusion Models from Precise Learning Curves

8. Sampling in High-Dimensions using Stochastic Interpolants and Forward-Backward Stochastic Differential Equations

9. LITE: Efficiently Estimating Gaussian Probability of Maximality

10. Beyond R-barycenters: an effective averaging method on Stiefel and Grassmann manifolds

11. Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach

12. Multiplayer Federated Learning: Reaching Equilibrium with Less Communication

13. Cosmological Parameter Estimation with Sequential Linear Simulation-based Inference

14. jinns: a JAX Library for Physics-Informed Neural Networks

15. Energy-Efficient Sampling Using Stochastic Magnetic Tunnel Junctions

16. Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective

17. Equivariant Denoisers for Image Restoration

18. Kernel-Based Optimal Control: An Infinitesimal Generator Approach

19. On the Robustness of the Successive Projection Algorithm

20. Deployment of ARX Models for Thermal Forecasting in Power Electronics Boards Using WBG Semiconductors

21. Harnessing Superclasses for Learning from Hierarchical Databases

22. Effect sizes as a statistical feature-selector-based learning to detect breast cancer

23. Variational Bayes Portfolio Construction

24. Generating Highly Designable Proteins with Geometric Algebra Flow Matching

25. Differentially private and decentralized randomized power method

26. A mixture representation of the spectral distribution of isotropic kernels with application to random Fourier features

27. The impact of MRI image quality on statistical and predictive analysis on voxel based morphology

28. An unified approach to link prediction in collaboration networks

29. Node Regression on Latent Position Random Graphs via Local Averaging

30. Context is Key: A Benchmark for Forecasting with Essential Textual Information

31. Scalable Implicit Graphon Learning

32. Hypothesis Testing the Circuit Hypothesis in LLMs

33. Orthogonal Nonnegative Matrix Factorization with the Kullback-Leibler divergence

34. Data Taggants: Dataset Ownership Verification via Harmless Targeted Data Poisoning

35. Long-Context Linear System Identification

36. Leaf Stripping on Uniform Attachment Trees

37. Model Predictive Control is Almost Optimal for Restless Bandit

38. Density estimation with LLMs: a geometric investigation of in-context learning trajectories

39. Learning from negative feedback, or positive feedback or both

40. Large Language Models as Markov Chains

41. Simplicity bias and optimization threshold in two-layer ReLU networks

42. End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic data

43. Cartan moving frames and the data manifolds

44. Sample Complexity Bounds for Linear System Identification from a Finite Set

45. Optimal level set estimation for non-parametric tournament and crowdsourcing problems

46. Data-Driven Optimal Feedback Laws via Kernel Mean Embeddings

47. Medical Knowledge Integration into Reinforcement Learning Algorithms for Dynamic Treatment Regimes

48. Implicit Bias of Mirror Flow on Separable Data

49. Active clustering with bandit feedback

50. Treeffuser: Probabilistic Predictions via Conditional Diffusions with Gradient-Boosted Trees