4 papers
Generalization Properties of Score-matching Diffusion Models for Intrinsically Low-dimensional Data
Saptarshi Chakraborty, Quentin Berthet, Peter L. Bartlett
Despite the remarkable empirical success of score-based diffusion models, their statistical guarantees remain underdeveloped. Existing analyses often provide pessimistic convergenc…
A Statistical Analysis of Deep Federated Learning for Intrinsically Low-dimensional Data
Saptarshi Chakraborty, Peter L. Bartlett
Despite significant research on the optimization aspects of federated learning, the exploration of generalization error, especially in the realm of heterogeneous federated learning…
On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension
Saptarshi Chakraborty, Peter L. Bartlett
Despite the remarkable empirical successes of Generative Adversarial Networks (GANs), the theoretical guarantees for their statistical accuracy remain rather pessimistic. In partic…
A Statistical Analysis for Supervised Deep Learning with Exponential Families for Intrinsically Low-dimensional Data
Saptarshi Chakraborty, Peter L. Bartlett
Recent advances have revealed that the rate of convergence of the expected test error in deep supervised learning decays as a function of the intrinsic dimension and not the dimens…