50 citations
- Accenture (United States)US3 papers
- University College LondonGB2 papers
- American UniversityUS1 paper
- Astana Medical UniversityKZ1 paper
- California Institute of Integral StudiesUS1 paper
- École des hautes études en sciences socialesFR1 paper
- École Polytechnique Fédérale de LausanneCH1 paper
- Georgia Institute of TechnologyUS1 paper
- GoodAI (Czechia)CZ1 paper
- Independent University of MoscowRU1 paper
- Indian Institute of Technology IndoreIN1 paper
- Indian Institute of Technology PatnaIN1 paper
7 papers · 1 filter
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods
Peru Bhardwaj, John Kelleher, Luca Costabello +1
Despite the widespread use of Knowledge Graph Embeddings (KGE), little is known about the security vulnerabilities that might disrupt their intended behaviour. We study data poison…
Accenture at CheckThat! 2021: Interesting claim identification and ranking with contextually sensitive lexical training data augmentation
Evan Williams, Paul Rodrigues, Sieu Tran
This paper discusses the approach used by the Accenture Team for CLEF2021 CheckThat! Lab, Task 1, to identify whether a claim made in social media would be interesting to a wide au…
Learning Embeddings from Knowledge Graphs With Numeric Edge Attributes
Sumit Pai, Luca Costabello
Numeric values associated to edges of a knowledge graph have been used to represent uncertainty, edge importance, and even out-of-band knowledge in a growing number of scenarios, r…
VeriMedi: Pill Identification using Proxy-based Deep Metric Learning and Exact Solution
Tekin Evrim Ozmermer, Viktors Roze, Stanislavs Hilcuks +1
We present the system that we have developed for the identification and verification of pills using images that are taken by the VeriMedi device. The VeriMedi device is an Internet…
Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties
Lisa Schut, Oscar Key, Rory McGrath +4
Counterfactual explanations (CEs) are a practical tool for demonstrating why machine learning classifiers make particular decisions. For CEs to be useful, it is important that they…
A Framework for Enabling Safe and Resilient Food Factories for the Public Feeding Programs
Nataraj Kuntagod, Sanjay Podder, Satya Sai Srinivas Abbabathula +3
Public feeding programs continue to be a major source of nutrition to a large part of the population across the world. Any disruption to these activities, like the one during the C…