Search Results for author: Derek Doran

Found 18 papers, 5 papers with code

Explainable Deep Learning: A Field Guide for the Uninitiated

no code implementations30 Apr 2020 Gabrielle Ras, Ning Xie, Marcel van Gerven, Derek Doran

The field guide: i) Introduces three simple dimensions defining the space of foundational methods that contribute to explainable deep learning, ii) discusses the evaluations for model explanations, iii) places explainability in the context of other related deep learning research areas, and iv) finally elaborates on user-oriented explanation designing and potential future directions on explainable deep learning.

Decision Making

Contextual Grounding of Natural Language Entities in Images

1 code implementation5 Nov 2019 Farley Lai, Ning Xie, Derek Doran, Asim Kadav

Next, the model learns the contextual representations of the text tokens and image objects through layers of high-order interaction respectively.

Language Modelling Masked Language Modeling

Fuzzy Rough Set Feature Selection to Enhance Phishing Attack Detection

no code implementations13 Mar 2019 Mahdieh Zabihimayvan, Derek Doran

To evaluate the FRS feature selection in developing a generalizable phishing detection, the classifiers are trained by a separate out-of-sample data set of 14, 000 website samples.

feature selection

Visual Entailment: A Novel Task for Fine-Grained Image Understanding

1 code implementation20 Jan 2019 Ning Xie, Farley Lai, Derek Doran, Asim Kadav

We evaluate various existing VQA baselines and build a model called Explainable Visual Entailment (EVE) system to address the VE task.

Question Answering Sentence +3

Visual Entailment Task for Visually-Grounded Language Learning

1 code implementation26 Nov 2018 Ning Xie, Farley Lai, Derek Doran, Asim Kadav

We introduce a new inference task - Visual Entailment (VE) - which differs from traditional Textual Entailment (TE) tasks whereby a premise is defined by an image, rather than a natural language sentence as in TE tasks.

Grounded language learning Question Answering +3

HELOC Applicant Risk Performance Evaluation by Topological Hierarchical Decomposition

no code implementations26 Nov 2018 Kyle Brown, Derek Doran, Ryan Kramer, Brad Reynolds

Strong regulations in the financial industry mean that any decisions based on machine learning need to be explained.

BIG-bench Machine Learning

Reasoning over RDF Knowledge Bases using Deep Learning

2 code implementations9 Nov 2018 Monireh Ebrahimi, Md. Kamruzzaman Sarker, Federico Bianchi, Ning Xie, Derek Doran, Pascal Hitzler

Semantic Web knowledge representation standards, and in particular RDF and OWL, often come endowed with a formal semantics which is considered to be of fundamental importance for the field.

Knowledge Graphs

Deep Neural Ranking for Crowdsourced Geopolitical Event Forecasting

no code implementations23 Oct 2018 Giuseppe Nebbione, Derek Doran, Srikanth Nadella, Brandon Minnery

We develop a forecast aggregation model that integrates topical information about a question, meta-data about a pair of forecasters, and their predictions in a deep siamese neural network that decides which forecasters' predictions are more likely to be close to the correct response.

Realistic Traffic Generation for Web Robots

no code implementations15 Dec 2017 Kyle Brown, Derek Doran

Web traffic generation is a classic research problem, no generator accounts for the characteristics of web robots or crawlers that are now the dominant source of traffic to a web server.

Intrinsic Point of Interest Discovery from Trajectory Data

no code implementations14 Dec 2017 Matthew Piekenbrock, Derek Doran

Spatial and temporal aspects are qualities of any trajectory database, making the framework applicable to data from any domain and of any resolution.

Relating Input Concepts to Convolutional Neural Network Decisions

no code implementations21 Nov 2017 Ning Xie, Md. Kamruzzaman Sarker, Derek Doran, Pascal Hitzler, Michael Raymer

Many current methods to interpret convolutional neural networks (CNNs) use visualization techniques and words to highlight concepts of the input seemingly relevant to a CNN's decision.

Decision Making Scene Recognition

Explaining Trained Neural Networks with Semantic Web Technologies: First Steps

no code implementations11 Oct 2017 Md. Kamruzzaman Sarker, Ning Xie, Derek Doran, Michael Raymer, Pascal Hitzler

The ever increasing prevalence of publicly available structured data on the World Wide Web enables new applications in a variety of domains.

What Does Explainable AI Really Mean? A New Conceptualization of Perspectives

no code implementations2 Oct 2017 Derek Doran, Sarah Schulz, Tarek R. Besold

We characterize three notions of explainable AI that cut across research fields: opaque systems that offer no insight into its algo- rithmic mechanisms; interpretable systems where users can mathemat- ically analyze its algorithmic mechanisms; and comprehensible systems that emit symbols enabling user-driven explanations of how a conclusion is reached.

EmojiNet: An Open Service and API for Emoji Sense Discovery

no code implementations14 Jul 2017 Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran

This paper presents the release of EmojiNet, the largest machine-readable emoji sense inventory that links Unicode emoji representations to their English meanings extracted from the Web.

A Semantics-Based Measure of Emoji Similarity

2 code implementations14 Jul 2017 Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran

This paper presents a comprehensive analysis of the semantic similarity of emoji through embedding models that are learned over machine-readable emoji meanings in the EmojiNet knowledge base.

Semantic Similarity Semantic Textual Similarity +1

Finding Street Gang Members on Twitter

no code implementations29 Oct 2016 Lakshika Balasuriya, Sanjaya Wijeratne, Derek Doran, Amit Sheth

A review of these profiles establishes differences in the language, images, YouTube links, and emojis gang members use compared to the rest of the Twitter population.

EmojiNet: Building a Machine Readable Sense Inventory for Emoji

no code implementations25 Oct 2016 Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran

It is automatically constructed by integrating multiple emoji resources with BabelNet, which is the most comprehensive multilingual sense inventory available to date.

Word Sense Disambiguation

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