Minimum Error Rate Training is the algorithm for log-linear model parameter training most used in state-of-the-art Statistical Machine Translation systems. In its original formula...
Abstract— Sampling-based algorithms have dramatically improved the state of the art in robotic motion planning. However, they make restrictive assumptions that limit their applic...
In this work, we give an algorithm that infers Regular Trace Languages. Trace languages can be seen as regular languages that are closed under a partial commutation relation called...
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse s...
Laurent Jacques, Jason N. Laska, Petros Boufounos,...
Measurement, collection, and interpretation of network usage data commonly involves multiple stage of sampling and aggregation. Examples include sampling packets, aggregating them...
Edith Cohen, Nick G. Duffield, Carsten Lund, Mikke...