A novel sparse resultant-based approach to generating polynomial solvers based on adding an extra equation of a special form and transforming the resultant matrix constraint to a regular eigenvalue …

The resultant dataset accumulates over 2000 hours of driving videos spanning areas all over the world with diverse weather conditions and traffic scenarios. Inheriting the merits from recent latent diffusion …

We call the resultant K cluster centers local proto-types — represent local semantics like the “head”, “leg”, and “body” of “sheep”. Given a new image of the class, we compare its unpooled features to …

cenes: Here we show results from the synthetic experiment presented in the main pa-per. We studied the numerical stability of the new resultant-based solver for the problem of estimating the relative …

In this paper we study an alternative algebraic method for solving systems of polynomial equations, i.e., the sparse resultant-based method and propose a novel approach to convert the resultant constraint …

To solve the resultant optimization problem, we design an efficient algorithm of linear complexity.Moreover, extensive experiments are conducted and corresponding results well support …

Specifically, to solve the resultant optimization problem, we propose a new algorithm which is not only efficient but also theoretically guaranteed to obtain a globally optimal solution.

However despite the benefits of the resultant adaptive network existing works rely on time-intensive quantization-aware training with full access to the original training pairs to learn the appropriate bit …

The resultant ensemble of randomly pruned SASD models can possess better generalization capability than the orig-inal SASD model. However, generating adversarial exam-ples with an ensemble model …

Subsequently, we pre-train a vision-side transformer by incorporating these newly extracted tokens and aligning the resultant embeddings with caption embeddings from a text-side encoder.