2 citations · 5 across the 36 of their papers we have counts for
6 papers · 1 filter
Privacy Preserving Gossip Learning
Erkan Bayram, Mohamed-Ali Belabbas, Tamer Başar
We propose a decentralized privacy-preserving learning algorithm in which each agent holds a single private sample and a shared model. Samples are learned sequentially, and each up…
Control Disturbance Rejection in Neural ODEs
Erkan Bayram, Mohamed-Ali Belabbas, Tamer Başar
In this paper, we propose an iterative training algorithm for Neural ODEs that provides models resilient to control (parameter) disturbances. The method builds on our earlier work…
Geometric Foundations of Tuning without Forgetting in Neural ODEs
Erkan Bayram, Mohamed-Ali Belabbas, Tamer Başar
In our earlier work, we introduced the principle of Tuning without Forgetting (TwF) for sequential training of neural ODEs, where training samples are added iteratively and paramet…
Structure Matters: Dynamic Policy Gradient
Sara Klein, Xiangyuan Zhang, Tamer Başar +2
In this work, we study -discounted infinite-horizon tabular Markov decision processes (MDPs) and introduce a framework called dynamic policy gradient (DynPG). The framework dire…
Control Theoretic Approach to Fine-Tuning and Transfer Learning
Erkan Bayram, Shenyu Liu, Mohamed-Ali Belabbas +1
Given a training set in the form of a paired , we say that the control system has learned the paired set via the control if the s…
Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective
Muhammad Aneeq uz Zaman, Alec Koppel, Mathieu Laurière +1
We address in this paper Reinforcement Learning (RL) among agents that are grouped into teams such that there is cooperation within each team but general-sum (non-zero sum) competi…