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 …

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 …

WS obtains an approximate ensemble of numerous pruned models to per-form model augmentation, which can be conveniently syn-ergized with SASD to elevate the source …

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 …

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 …

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

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

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 …

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 …

The resultant distribution can then be sampled to generate likely completions, each of which exhibits plausible shape details, while being faithful to the input.