5 papers
Heavy-tailed Contamination is Easier than Adversarial Contamination
Yeshwanth Cherapanamjeri, Daniel Lee
A large body of work in the statistics and computer science communities dating back to Huber (Huber, 1960) has led to statistically and computationally efficient outlier-robust est…
How much is a noisy image worth? Data Scaling Laws for Ambient Diffusion
Giannis Daras, Yeshwanth Cherapanamjeri, Constantinos Daskalakis
The quality of generative models depends on the quality of the data they are trained on. Creating large-scale, high-quality datasets is often expensive and sometimes impossible, e.…
Statistical Barriers to Affine-equivariant Estimation
Zihao Chen, Yeshwanth Cherapanamjeri
We investigate the quantitative performance of affine-equivariant estimators for robust mean estimation. As a natural stability requirement, the construction of such affine-equivar…
Optimal PAC Bounds Without Uniform Convergence
Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty +1
In statistical learning theory, determining the sample complexity of realizable binary classification for VC classes was a long-standing open problem. The results of Simon and Hann…
Robust Algorithms on Adaptive Inputs from Bounded Adversaries
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff +3
We study dynamic algorithms robust to adaptive input generated from sources with bounded capabilities, such as sparsity or limited interaction. For example, we consider robust line…