96 citations · 298 across the 54 of their papers we have counts for
4 papers · 2 filters
Lifting Finite-Sample Gaussian Approximation of Wide Neural Networks to Functional Convergence
Luis Wiederhold, Nil Ayday, Debarghya Ghoshdastidar
Randomly initialised neural networks of width converge to Gaussian processes as , with two types of quantitative bounds characterising this convergence. Finite-sa…
An Analysis of Self-supervised Pre-training with Dependent Samples
Maximilian Fleissner, Debarghya Ghoshdastidar, Samory Kpotufe
Self-supervised learning relies on so-called data augmentations of unlabeled datapoints --- for example, masking random pixels in an image --- that should leave the…
Gaussian Process Limit Reveals Structural Benefits of Graph Transformers
Nil Ayday, Lingchu Yang, Debarghya Ghoshdastidar
Graph transformers are the state-of-the-art for learning from graph-structured data and are empirically known to avoid several pitfalls of message-passing architectures. However, t…
Nonparametric Kernel Clustering with Bandit Feedback
Victor Thuot, Sebastian Vogt, Debarghya Ghoshdastidar +1
Clustering with bandit feedback refers to the problem of partitioning the arms of an -armed stochastic bandit according to their underlying distributions, based on noisy observa…