Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...
In previous work, a water-filling algorithm was proposed which sought to minimize the mean square error (MSE) at any given time by optimally choosing the gains (i.e. step-sizes) ...
Approximation has been shown to be an eective method for reducing the time and space costs of solving various oorplan area minimization problems. In this paper, we present several...
FPGA-based computing engines have become a promising option for the implementation of computationally intensive applications due to high flexibility and parallelism. However, one...
Qiang Liu, George A. Constantinides, Konstantinos ...
: In this paper, we present a fast and simple algorithm for constructing a minimal acyclic deterministic finite automaton from a finite set of words. Such automata are useful in a ...