DPOP is an algorithm for distributed constraint optimization which has, as main drawback, the exponential size of some of its messages. Recently, some algorithms for distributed c...
Context is critical for minimising ambiguity in object de-
tection. In this work, a novel context modelling framework
is proposed without the need of any prior scene segmen-
tat...
—Broadcast presents a special challenge for Wireless Sensor Networks (WSNs). In some situation such as time synchronization or building routing path, broadcasting messages must b...
— In this paper, a family of low-density parity-check (LDPC) degree distributions, whose decoding threshold on the binary erasure channel (BEC) admits a simple closed form, is pr...
We extend our recent work on relevant subtask learning, a new variant of multitask learning where the goal is to learn a good classifier for a task-of-interest with too few train...