7 papers
Learnable Sequential Memory in Coupled Oscillator Networks
Taosha Guo, Fabio Pasqualetti
The Hopfield network established that static memories can be stored as energy minima of a recurrent dynamical system, yet real intelligent agents must navigate \emph{sequences} of…
Oscillator-Based Associative Memory with Exponential Capacity: Theory, Algorithms, and Hardware Implementation
Arie Ogranovich, Taosha Guo, Arvind R. Venkatakrishnan +3
Associative memory systems enable content-addressable storage and retrieval of patterns, a capability central to biological neural computation and artificial intelligence. Classica…
Global Optimization Through Heterogeneous Oscillator Ising Machines
Ahmed Allibhoy, Arthur N. Montanari, Fabio Pasqualetti +1
Oscillator Ising machines (OIMs) are networks of coupled oscillators that seek the minimum energy state of an Ising model. Since many NP-hard problems are equivalent to the minimiz…
Transfer Learning for LQR Control
Taosha Guo, Fabio Pasqualetti
In this paper, we study a transfer learning framework for Linear Quadratic Regulator (LQR) control, where (i) the dynamics of the system of interest (target system) are unknown and…
Oscillatory Associative Memory with Exponential Capacity
Taosha Guo, Arie Ogranovich, Arvind R. Venkatakrishnan +3
The slowing of Moore's law and the increasing energy demands of machine learning present critical challenges for both the hardware and machine learning communities, and drive the d…
Online Optimization with Unknown Time-varying Parameters
Shivanshu Tripathi, Abed AlRahman Al Makdah, Fabio Pasqualetti
In this paper, we study optimization problems where the cost function contains time-varying parameters that are unmeasurable and evolve according to linear, yet unknown, dynamics.…