This work proposes a novel method named SGD(m) with residuals (RSGD(m), which leads to a performance boost of both the convergence and generalization of SGD ...

May 29, 2024 · We introduce a novel online (or sequential) nonlinear prediction approach that incorporates the residuals, ie, prediction errors in the past observations, as ...

We investigate asymptotic and finite sample properties of solutions obtained using Wasserstein, sample robust optimization, and phi-divergence-based ambiguity ...

In this work, we propose a new one-point feedback method for online optimization that estimates the objective function gradient using the residual between two ...

Feb 25, 2023 · In this article, we propose a general framework, called RI-GAN, that exploits residual and illumination using generative adversarial networks (GANs).

May 29, 2024 · The algorithm exploits the changes in the previous time steps through residual terms between boosting steps by jointly optimizing the model ...

The key idea is that we can effectively exploit the self-similarity by applying a single common operation to multiple sub- sequences with different resolutions.

It imports arbitrary crystal structures, generates artificial diffraction data, and calculates and investigates the residual function in parameter space. The ...

Feb 17, 2020 · We study the decision processes underlying such exploration/exploitation trade-offs using a novel card selection task that captures the common situation of ...

Feb 8, 2020 · We derive a new for RL method, BRPO, which learns both the policy and allowable deviation that jointly maximize a lower bound on policy performance.