3,300 research outputs found
Story Cloze Ending Selection Baselines and Data Examination
This paper describes two supervised baseline systems for the Story Cloze Test
Shared Task (Mostafazadeh et al., 2016a). We first build a classifier using
features based on word embeddings and semantic similarity computation. We
further implement a neural LSTM system with different encoding strategies that
try to model the relation between the story and the provided endings. Our
experiments show that a model using representation features based on average
word embedding vectors over the given story words and the candidate ending
sentences words, joint with similarity features between the story and candidate
ending representations performed better than the neural models. Our best model
achieves an accuracy of 72.42, ranking 3rd in the official evaluation.Comment: Submission for the LSDSem 2017 - Linking Models of Lexical,
Sentential and Discourse-level Semantics - Shared Tas
Neural Skill Transfer from Supervised Language Tasks to Reading Comprehension
Reading comprehension is a challenging task in natural language processing
and requires a set of skills to be solved. While current approaches focus on
solving the task as a whole, in this paper, we propose to use a neural network
`skill' transfer approach. We transfer knowledge from several lower-level
language tasks (skills) including textual entailment, named entity recognition,
paraphrase detection and question type classification into the reading
comprehension model.
We conduct an empirical evaluation and show that transferring language skill
knowledge leads to significant improvements for the task with much fewer steps
compared to the baseline model. We also show that the skill transfer approach
is effective even with small amounts of training data. Another finding of this
work is that using token-wise deep label supervision for text classification
improves the performance of transfer learning
An explicit Euler scheme with strong rate of convergence for financial SDEs with non-Lipschitz coefficients
We consider the approximation of stochastic differential equations (SDEs)
with non-Lipschitz drift or diffusion coefficients. We present a modified
explicit Euler-Maruyama discretisation scheme that allows us to prove strong
convergence, with a rate. Under some regularity and integrability conditions,
we obtain the optimal strong error rate. We apply this scheme to SDEs widely
used in the mathematical finance literature, including the
Cox-Ingersoll-Ross~(CIR), the 3/2 and the Ait-Sahalia models, as well as a
family of mean-reverting processes with locally smooth coefficients. We
numerically illustrate the strong convergence of the scheme and demonstrate its
efficiency in a multilevel Monte Carlo setting.Comment: 36 pages, 17 figures, 2 table
Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering
We present a new kind of question answering dataset, OpenBookQA, modeled
after open book exams for assessing human understanding of a subject. The open
book that comes with our questions is a set of 1329 elementary level science
facts. Roughly 6000 questions probe an understanding of these facts and their
application to novel situations. This requires combining an open book fact
(e.g., metals conduct electricity) with broad common knowledge (e.g., a suit of
armor is made of metal) obtained from other sources. While existing QA datasets
over documents or knowledge bases, being generally self-contained, focus on
linguistic understanding, OpenBookQA probes a deeper understanding of both the
topic---in the context of common knowledge---and the language it is expressed
in. Human performance on OpenBookQA is close to 92%, but many state-of-the-art
pre-trained QA methods perform surprisingly poorly, worse than several simple
neural baselines we develop. Our oracle experiments designed to circumvent the
knowledge retrieval bottleneck demonstrate the value of both the open book and
additional facts. We leave it as a challenge to solve the retrieval problem in
this multi-hop setting and to close the large gap to human performance.Comment: Published as conference long paper at EMNLP 201
Simultaneous Implementation Of Ssl And Ipsec Protocols For Remote Vpn Connection
A Virtual Private Network is a wide spread technology for connecting remote users and locations to the main core network. It has number of benefits such as cost-efficiency and security. SSL and IPSec are the most popular VPN protocols employed by large number of organizations. Each protocol has its benefits and disadvantages. Simultaneous SSL and IPSec implementation delivers efficient and flexible solution for companies’ with heterogeneous remote connection needs. On the other hand, employing two different VPN technologies opens questions about compatibility, performance, and drawbacks especially if they are utilized by one network device. The study examines the behavior of the two VPN protocols implemented in one edge network device, ASA 5510 security appliance. It follows the configuration process as well as the effect of the VPN protocols on the ASA performance including routing functions, firewall access lists, and network address translation abilities. The paper also presents the cost effect and the maintenance requirements for utilizing SSL and IPSec in one edge network security devic
Techno-economic analysis of residential thermal flexibility for demand side management
The continuing rise in solar and wind production leads to an increasing demand of flexibility to stabilize the electricity grid. Furthermore, we can assume a gradual but intensive rise in the use of electrical heatpumps for household spatial heating, for different reasons. Therefore, this paper investigates the feasibility and viability of entering the flexibility market by aggregating residential thermal loads. For this research, a dataset of 200 dwellings in the Netherlands, equipped with a heatpump and smart metering infrastructure, is analysed. By means of a greybox modeling approach, a thermal model and control framework have been set up for every house, in order to identify the load shift potential and the accompanying cost of providing flexibility for the houses. We find that thermal flexibility is asymmetric: downwards flexibility is, apart from much more dependent on outdoor temperature than upwards flexibility, strictly lower than upwards flexibility. The cost for downwards flexibility is strictly negative in terms of the prosumer. Concerning upwards flexibility, the cost is most of the time positive. Moreover, it can be concluded that there is a potentially viable business case for the flexibility aggregator
Numerical schemes and Monte Carlo techniques for Greeks in stochastic volatility models
The main objective of this thesis is to propose approximations to option sensitivities in stochastic volatility models. The first part explores sequential Monte Carlo techniques for approximating the latent state in a Hidden Markov Model. These techniques are applied to the computation of Greeks by adapting the likelihood ratio method. Convergence of the Greek estimates is proved and tracking of option prices is performed in a stochastic volatility model.
The second part defines a class of approximate Greek weights and provides high-order approximations and justification for extrapolation techniques. Under certain regularity assumptions on the value function of the problem, Greek approximations are proved for a fully implementable Monte Carlo framework, using weak Taylor discretisation schemes. The variance and bias are studied for the Delta and Gamma, when using such discrete-time approximations.
The final part of the thesis introduces a modified explicit Euler scheme for stochastic differential equations with non-Lipschitz continuous drift or diffusion; a strong rate of convergence is proved. The literature on discretisation techniques for stochastic differential equations has been motivational for the development of techniques preserving the explicitness of the algorithm. Stochastic differential equations in the mathematical finance literature, including the Cox-Ingersoll-Ross, the 3/2 and the Ait-Sahalia models can be discretised, with a strong rate of convergence proved, which is a requirement for multilevel Monte Carlo techniques.Open Acces
A Review and Critique of John McKnight`s Theory of `The Careless Society`
John McKnight`s theory of the Careless Society is key to understanding post-industrial society trends in organization and delivery of health and social services in communities. The article presents the theory and its connections with other influential critiques of modern institutions. The theory is analyzed and critiqued itself from a sociological perspective, drawing upon alternative points of view. McKnight`s work can be very useful to institutions and professionals offering health, social and education services.John McKnight`s theory of the Careless Society is key to understanding post-industrial society trends in organization and delivery of health and social services in communities. The article presents the theory and itsconnections with other influential critiques of modern institutions. The theory is analyzed and critiqued itself from a sociological perspective, drawing upon alternative points of view. McKnight`s work can be very useful to institutions and professionals offering health, social and education services
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