no code implementations • 8 May 2023 • Harshat Kumar, Alejandro Parada-Mayorga, Alejandro Ribeiro
We show that traditional group convolutions are one particular instantiation of a more general Lie group algebra homomorphism associated to an algebraic signal model rooted in the Lie group algebra $L^{1}(G)$ for given Lie group $G$.
no code implementations • 31 Oct 2022 • Harshat Kumar, Alejandro Parada-Mayorga, Alejandro Ribeiro
Group convolutional neural networks are a useful tool for utilizing symmetries known to be in a signal; however, they require that the signal is defined on the group itself.
no code implementations • 12 Jun 2020 • Harshat Kumar, Dionysios S. Kalogerias, George J. Pappas, Alejandro Ribeiro
Deterministic Policy Gradient (DPG) removes a level of randomness from standard randomized-action Policy Gradient (PG), and demonstrates substantial empirical success for tackling complex dynamic problems involving Markov decision processes.
no code implementations • 18 Oct 2019 • Harshat Kumar, Alec Koppel, Alejandro Ribeiro
Actor-critic algorithms combine the merits of both approaches by alternating between steps to estimate the value function and policy gradient updates.