Interpretation of Natural Language Rules in Conversational Machine Reading

Most work in machine reading focuses on question answering problems where the answer is directly expressed in the text to read. However, many real-world question answering problems require the reading of text not because it contains the literal answer, but because it contains a recipe to derive an answer together with the reader's background knowledge. One example is the task of interpreting regulations to answer "Can I...?" or "Do I have to...?" questions such as "I am working in Canada. Do I have to carry on paying UK National Insurance?" after reading a UK government website about this topic. This task requires both the interpretation of rules and the application of background knowledge. It is further complicated due to the fact that, in practice, most questions are underspecified, and a human assistant will regularly have to ask clarification questions such as "How long have you been working abroad?" when the answer cannot be directly derived from the question and text. In this paper, we formalise this task and develop a crowd-sourcing strategy to collect 32k task instances based on real-world rules and crowd-generated questions and scenarios. We analyse the challenges of this task and assess its difficulty by evaluating the performance of rule-based and machine-learning baselines. We observe promising results when no background knowledge is necessary, and substantial room for improvement whenever background knowledge is needed.Comment: EMNLP 201

A tradeoff between robustness to environmental fluctuations and speed of evolution

Organisms must cope with both short- and long-term environmental changes to persist. In this study we investigated whether life histories trade-off between their robustness to short-term environmental perturbations and their ability to evolve directional trait changes. We could confirm the tradeoff by modeling the eco-evolutionary dynamics of life-histories along the fast-slow pace-of-life continuum. Offspring dormancy and high adult survival rates allowed for large population sizes to be maintained in face of interannual environmental fluctuations but limited the speed of trait evolution with ongoing environmental change. In contrast, precocious offspring maturation and short-living adults promoted evolvability while lowering demographic robustness. This tradeoff had immediate consequences on extinction dynamics in variable environments. High evolvability allowed short-lived species to cope with long-lasting gradual environmental change, but came at the expense of more pronounced population declines and extinction rates from environmental variability. Higher robustness of slow life-histories helped them persist better on short timescales

Gravitational lensing reveals ionizing ultraviolet photons escaping from a distant galaxy

During the epoch of reionisation, neutral gas in the early Universe was ionized by hard ultraviolet radiation emitted by young stars in the first galaxies. To do so, ionizing ultraviolet photons must escape from the host galaxy. We present Hubble Space Telescope observations of the gravitationally lensed galaxy PSZ1-ARC G311.6602-18.4624, revealing bright, multiply-imaged ionizing photon escape from a compact star-forming region through a narrow channel in an optically thick gas. The gravitational lensing magnification shows how ionizing photons escape this galaxy, contributing to the re-ionization of the Universe. The multiple sight lines to the source probe absorption by intergalactic neutral hydrogen on scales of no more than a few hundred, perhaps even less than ten, parsec.Comment: 17 pages, 9 figures. Published in Scienc

Soft Control of Self-organized Locally Interacting Brownian Planar Agents

This contribution is addressed to the dynamics of heterogeneous interacting agents evolving on the plane. Heterogeneity is due to the presence of an unfiltered externally controllable fellow, a shill, which via mutual interactions ultimately drives (i.e. soft controls) the whole society towards a given goal. We are able to calculate relevant dynamic characteristics of this controllable agent. This opens the possibility to optimize the soft controlling of a whole society by infiltrating it with a properly designed shill. Numerical results fully corroborate our theoretical findings

Intearcting Brownian Swarms: Some Analytical Results

We consider the dynamics of swarms of scalar Brownian agents subject to local imitation mechanisms implemented using mutual rank-based interactions. For appropriate values of the underlying control parameters, the swarm propagates tightly and the distances separating successive agents are iid exponential random variables. Implicitly, the implementation of rank-based mutual interactions, requires that agents have infinite interaction ranges. Using the probabilistic size of the swarm’s support, we analytically estimate the critical interaction range below that flocked swarms cannot survive. In the second part of the paper, we consider the interactions between two flocked swarms of Brownian agents with finite interaction ranges. Both swarms travel with different barycentric velocities, and agents from both swarms indifferently interact with each other. For appropriate initial configurations, both swarms eventually collide (i.e., all agents interact). Depending on the values of the control parameters, one of the following patterns emerges after collision: (i) Both swarms remain essentially flocked, or (ii) the swarms become ultimately quasi-free and recover their nominal barycentric speeds. We derive a set of analytical flocking conditions based on the generalized rank-based Brownian motion. An extensive set of numerical simulations corroborates our analytical findings

Efficient implementation of atom-density representations

Physically motivated and mathematically robust atom-centered representations of molecular structures are key to the success of modern atomistic machine learning. They lie at the foundation of a wide range of methods to predict the properties of both materials and molecules and to explore and visualize their chemical structures and compositions. Recently, it has become clear that many of the most effective representations share a fundamental formal connection. They can all be expressed as a discretization of n-body correlation functions of the local atom density, suggesting the opportunity of standardizing and, more importantly, optimizing their evaluation. We present an implementation, named librascal, whose modular design lends itself both to developing refinements to the density-based formalism and to rapid prototyping for new developments of rotationally equivariant atomistic representations. As an example, we discuss smooth overlap of atomic position (SOAP) features, perhaps the most widely used member of this family of representations, to show how the expansion of the local density can be optimized for any choice of radial basis sets. We discuss the representation in the context of a kernel ridge regression model, commonly used with SOAP features, and analyze how the computational effort scales for each of the individual steps of the calculation. By applying data reduction techniques in feature space, we show how to reduce the total computational cost by a factor of up to 4 without affecting the model’s symmetry properties and without significantly impacting its accuracy

Factores determinantes de la morosidad del cliente del crédito consumo del banco Azteca - sucursal Trujillo, 2014 - 2016

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