12 citations · 18 across the 12 of their papers we have counts for
4 papers · 1 filter
Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise
Thanh Dang, Melih Barsbey, A K M Rokonuzzaman Sonet +3
Understanding the generalization properties of optimization algorithms under heavy-tailed noise has gained growing attention. However, the existing theoretical results mainly focus…
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares
Anant Raj, Melih Barsbey, Mert Gürbüzbalaban +2
Recent studies have shown that heavy tails can emerge in stochastic optimization and that the heaviness of the tails have links to the generalization error. While these studies hav…
Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks
Melih Barsbey, Milad Sefidgaran, Murat A. Erdogdu +2
Neural network compression techniques have become increasingly popular as they can drastically reduce the storage and computation requirements for very large networks. Recent empir…
Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns
Ali Taylan Cemgil, Mehmet Burak Kurutmaz, Sinan Yildirim +2
We introduce a dynamic generative model, Bayesian allocation model (BAM), which establishes explicit connections between nonnegative tensor factorization (NTF), graphical models of…