154 citations · 861 across the 94 of their papers we have counts for
8 papers · 1 filter
Finite Sample Identification of Bilinear Dynamical Systems
Yahya Sattar, Samet Oymak, Necmiye Ozay
Bilinear dynamical systems are ubiquitous in many different domains and they can also be used to approximate more general control-affine systems. This motivates the problem of lear…
Representation Learning for Context-Dependent Decision-Making
Yuzhen Qin, Tommaso Menara, Samet Oymak +2
Humans are capable of adjusting to changing environments flexibly and quickly. Empirical evidence has revealed that representation learning plays a crucial role in endowing humans…
FedNest: Federated Bilevel, Minimax, and Compositional Optimization
Davoud Ataee Tarzanagh, Mingchen Li, Christos Thrampoulidis +1
Standard federated optimization methods successfully apply to stochastic problems with single-level structure. However, many contemporary ML problems -- including adversarial robus…
System Identification via Nuclear Norm Regularization
Yue Sun, Samet Oymak, Maryam Fazel
This paper studies the problem of identifying low-order linear systems via Hankel nuclear norm regularization. Hankel regularization encourages the low-rankness of the Hankel matri…
Provable and Efficient Continual Representation Learning
Yingcong Li, Mingchen Li, M. Salman Asif +1
In continual learning (CL), the goal is to design models that can learn a sequence of tasks without catastrophic forgetting. While there is a rich set of techniques for CL, relativ…
Towards Sample-efficient Overparameterized Meta-learning
Yue Sun, Adhyyan Narang, Halil Ibrahim Gulluk +2
An overarching goal in machine learning is to build a generalizable model with few samples. To this end, overparameterization has been the subject of immense interest to explain th…