Pseudo-Labeling for Covariate Shift Adaptation

Transfer learning for weak-to-strong generalization

Open-Source and Science in the Era of Foundation Models

Transfer learning via local convergence rates of the nonparametric least squares estimator

How Transformers Learn Causal Structure with Gradient Descent

Session 2 - 2024 GSN Research Conference, May 18, 2024

Think Fast, Talk Smart: Communication Techniques

On Spurious Associations and LLM Alignment

Adaptive Data Collection via Autoregressive Generation

Diffusion-based Maximum Marginal Likelihood Estimation: Overdamped, Accelerated, and Proximal

Machine learning - Maximum likelihood and linear regression

Scalably Understanding AI with AI

The Solow Residual: Increasing Returns and Factor Utilization

Domain Adaptation-- 20 years of theory chasing practice

Lecture 8 - Data Splits, Models & Cross-Validation | Stanford CS229: Machine Learning (Autumn 2018)

The Data Addition Dilemma

Toward Understanding the Extrapolation of Nonlinear Models to Unseen Domains or the Whole Domain

Itamar Harel - Typical Interpolating Neural Nets Generalize Well (Heb)

Language-guided Adaptation

A Discrepancy-Based Theory of Adaptation

Causally motivated robustness to shortcut learning