Constrained decoding for text-level discourse parsing

International audienceThis paper presents a novel approach to document-based discourse analysis by performing a global A* search over the space of possible structures while optimizing a global criterion over the set of potential coherence relations. Existing approaches to discourse analysis have so far relied on greedy search strategies or restricted themselves to sentence-level discourse parsing. Another advantage of our approach, over other global alternatives (like Maximum Spanning Tree decoding algorithms), is its flexibility in being able to integrate constraints (including linguistically motivated ones like the Right Frontier Constraint). Finally, our paper provides the first discourse parsing system for French; our evaluation is carried out on the Annodis corpus. While using a lot less training data than earlier approaches than previous work on English, our system manages to achieve state-of-the-art results, with F1-scores of 66.2 and 46.8 when compared to unlabeled and labeled reference structures

Interdependent Scheduling Games

We propose a model of interdependent scheduling games in which each player controls a set of services that they schedule independently. A player is free to schedule his own services at any time; however, each of these services only begins to accrue reward for the player when all predecessor services, which may or may not be controlled by the same player, have been activated. This model, where players have interdependent services, is motivated by the problems faced in planning and coordinating large-scale infrastructures, e.g., restoring electricity and gas to residents after a natural disaster or providing medical care in a crisis when different agencies are responsible for the delivery of staff, equipment, and medicine. We undertake a game-theoretic analysis of this setting and in particular consider the issues of welfare maximization, computing best responses, Nash dynamics, and existence and computation of Nash equilibria.Comment: Accepted to IJCAI 201

An evaluation of the complete replacement of both fishmeal and fish oil in diets for juvenile Asian seabass, Lates calcarifer

An experiment was conducted to examine the potential for the complete replacement of fishmeal (FM) and fish oil (FO) in diets for barramundi,Lates calcarifer. A series of diets were formulated to the same digestible protein and energy specifications, but which were designed with FM inclusion levels at 300, 200, 100 or 0g/kg and FO at 100%, 30%, 15% or 0% of the added oil in the diets (4×4 factorial design). Ricebran oil was the alternative oil used in the growth study, while soybean meal and poultry meal were the main alternative protein sources used. For the growth study, fish of an initial weight of 154.4±1.1g were randomly allocated across 48 tanks (three replicates per treatment). After eight weeks, the average weight gain across all treatments was 187.7±2.3g/fish and feed conversion across all treatments averaged 1.04±0.01 feed/gain. A significant effect of FM on both feed intake and weight gain was observed, and this was observed as early as within the first few weeks, but no similar such effect was observed with FO. No effects were observed on protein deposition efficiency, though both lipid and energy deposition efficiencies were affected by FM level. The reduction in FO had a notable effect on the fatty acid composition of the diets and subsequently the fish fatty acid composition. Expression of key LC-PUFA metabolism genes in the liver of the fish was influenced by both FM and FO levels, but was only significant at the extremes of the treatment ranges. The results from this study demonstrate that there is clear potential to replace almost all the FM content of barramundi diets without loss of fish performance, up to and including diets with as little as 100g/kg fishmeal. Replacement of fish oil was more successful with the ability to completely replace all FO demonstrated at all but the lowest inclusion levels of FM. These results clearly demonstrate that the near complete replacement of both FM and FO in barramundi diets is a technical reality

Profiling Performance of Application Partitioning for Wearable Devices in Mobile Cloud and Fog Computing

Wearable devices have become essential in our daily activities. Due to battery constrains the use of computing, communication, and storage resources is limited. Mobile Cloud Computing (MCC) and the recently emerged Fog Computing (FC) paradigms unleash unprecedented opportunities to augment capabilities of wearables devices. Partitioning mobile applications and offloading computationally heavy tasks for execution to the cloud or edge of the network is the key. Offloading prolongs lifetime of the batteries and allows wearable devices to gain access to the rich and powerful set of computing and storage resources of the cloud/edge. In this paper, we experimentally evaluate and discuss rationale of application partitioning for MCC and FC. To experiment, we develop an Android-based application and benchmark energy and execution time performance of multiple partitioning scenarios. The results unveil architectural trade-offs that exist between the paradigms and devise guidelines for proper power management of service-centric Internet of Things (IoT) applications

Regularization in Image Non-Rigid Registration: I. Trade-off between Smoothness and Intensity Similarity

In this report, we first propose a new classification of non-rigid registratio- n algorithms into three main categories: in one hand, the geometric algorithms- , and in the other hand, intensity based methods that we split here into standard intensity-based (SIB) and pair-and-smooth (P&S) algorithms. We then focus on the subset of SIB and P&S algorithms that are competitive, i.e. that use a regularization energy which is minimized together with the intensity similarity energy. In SIB algorithms, these two energies are combined in a weighted sum, and thus the trade-off between them is direct. P&S algorithms alternates their respective minimization, leading to the characteristic two steps: pairing of points, and smoothing. We theoretically compare the behavior of SIB and P&S algorithms, and more precisely, we explain why in practice the smoothness of the transforms estimated by SIB algorithms is non-uniform, thus difficult to control, while P&S algorithms estimate a motion that is more uniformly smooth. We give an example illustrating this behavior. Very few P&S algorithms minimize a global energy. We therefore propose a new image registration energy whose minimization leads to a \PAS algorithm. This energy is general, and can use any existing similarity or regularization energy. Its behavior is also compared to the previous SIB and \PAS algorithms. This new energy allows uniformly smooth solutions, as for our previous P&S algorithm, while preventing registration of non-informative, noisy areas, as for SIB algorithms

Markov Decision Process Based Energy-Efficient On-Line Scheduling for Slice-Parallel Video Decoders on Multicore Systems

We consider the problem of energy-efficient on-line scheduling for slice-parallel video decoders on multicore systems. We assume that each of the processors are Dynamic Voltage Frequency Scaling (DVFS) enabled such that they can independently trade off performance for power, while taking the video decoding workload into account. In the past, scheduling and DVFS policies in multi-core systems have been formulated heuristically due to the inherent complexity of the on-line multicore scheduling problem. The key contribution of this report is that we rigorously formulate the problem as a Markov decision process (MDP), which simultaneously takes into account the on-line scheduling and per-core DVFS capabilities; the power consumption of the processor cores and caches; and the loss tolerant and dynamic nature of the video decoder's traffic. In particular, we model the video traffic using a Direct Acyclic Graph (DAG) to capture the precedence constraints among frames in a Group of Pictures (GOP) structure, while also accounting for the fact that frames have different display/decoding deadlines and non-deterministic decoding complexities. The objective of the MDP is to minimize long-term power consumption subject to a minimum Quality of Service (QoS) constraint related to the decoder's throughput. Although MDPs notoriously suffer from the curse of dimensionality, we show that, with appropriate simplifications and approximations, the complexity of the MDP can be mitigated. We implement a slice-parallel version of H.264 on a multiprocessor ARM (MPARM) virtual platform simulator, which provides cycle-accurate and bus signal-accurate simulation for different processors. We use this platform to generate realistic video decoding traces with which we evaluate the proposed on-line scheduling algorithm in Matlab