Ozan Şener

Unsupervised Transductive Domain Adaptation

2016 · arXiv (Cornell University)

Supervised learning with large scale labeled datasets and deep layered models has made a paradigm shift in diverse areas in learning and recognition. However, this approach still suffers generalization issues under the presence of a …

Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks

2020 · HAL (Le Centre pour la Communication Scientifique Directe)

Despite its success in a wide range of applications, characterizing the generalization properties of stochastic gradient descent (SGD) in non-convex deep learning problems is still an important challenge. While modeling the trajectories of SGD via …

Online Continual Learning Without the Storage Constraint

2023 · arXiv (Cornell University)

Traditional online continual learning (OCL) research has primarily focused on mitigating catastrophic forgetting with fixed and limited storage allocation throughout an agent's lifetime. However, a broad range of real-world applications are primarily constrained by computational …

Random Representations Outperform Online Continually Learned Representations

2024 · arXiv (Cornell University)

Continual learning has primarily focused on the issue of catastrophic forgetting and the associated stability-plasticity tradeoffs. However, little attention has been paid to the efficacy of continually learned representations, as representations are learned alongside classifiers …