IBM Research-Ireland

Articles related to people and projects from IBM Research-Ireland.

Harnessing Dialogue for Interactive Career Goal Recommendations

An interactive career goal recommender framework that uses dialogue to incorporate user feedback and interactively improve the recommendations.

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Biophysics-Inspired AI Uses Photons to Help Surgeons Identify Cancer

Biophysics-inspired AI tools would provide a richer amount of information to support intraoperative decisions of surgeons during removal of cancerous tissue.

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Privacy by Design for Financial Services Organizations in the GDPR Era

IBM Research understands data privacy for a modern business and has developed state-of-the-art solutions for protecting data in the GDPR era.

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On-Line Learning of Linear Dynamical Systems with Kalman Filters

A forecasting method that is applicable to arbitrary sequences and comes with a regret bound competing against a class of methods, which includes Kalman filters.

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Machine Learning in Action for the Humanitarian Sector

IBM and the Danish Refugee Council developed a machine learning system to help understand migration via strategic forecasts and scenario analysis.

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NeuNetS: Automating Neural Network Model Synthesis for Broader Adoption of AI

On December 14, 2018, IBM released NeuNetS, a fundamentally new capability that addresses the skills gap for the development of latest AI models for a wide range of business domains. NeuNetS uses AI to automatically synthesize deep neural network models faster and easier than ever before, scaling up the adoption of AI by companies and […]

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Could AI Help People Change Their Behaviour?

Throughout life, many of us develop unhealthy habits that may feel nearly impossible to change. To quit smoking, reduce alcohol consumption, eat a healthier diet, or become more physically active requires effort and the right state of mind. A team of behavioural scientists at University College London (UCL)  and researchers at IBM Research-Ireland are looking […]

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Algebraic Gradient-Based Solver (AGS): A Novel Solver for Approximate Marginal MAP Inference

There is a deep connection between planning and inference, and over the last decade, multiple researchers have introduced explicit reductions showing how stochastic planning can be solved using probabilistic inference with applications in robotics, scheduling, and environmental problems. However, heuristic methods and search are still the best-performing approaches for planning in large combinatorial state and […]

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A Robust AI-Centric Indoor Positioning System

In modern airport terminals, hospital complexes, office buildings, sports arenas, university campuses, and retail outlets, there is a growing market for convenient and easy-to-use applications for navigating indoors. With an expected growth rate of 30{ccf696850f4de51e8cea028aa388d2d2d2eef894571ad33a4aa3b26b43009887} by 2022, according to a MarketWatch Report, this demand is accelerated by the presence of advanced sensors in modern smartphones […]

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A Blockchain Architecture for the Internet of Things

Success in an Internet of Things application typically requires the connected, concerted operation and management of a large number of distributed and loosely coupled smart devices that identify and trust each other. While the IoT promises that this integration should ideally map to a decentralized hardware and software platform, current solutions are mostly based on […]

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Using AI to Design Deep Learning Architectures

Selecting the best architecture for deep learning architectures is typically a time-consuming process that requires expert input, but using AI can streamline this process. I am developing an evolutionary algorithm for architecture selection that is up to 50,000 times faster than other methods, with only a small increase in error rate. Deep learning models are […]

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Semantic Cache for AI-Enabled Image Analysis

The availability of high-resolution, inexpensive sensors has exponentially increased the amount of data being produced, which could overwhelm the existing Internet. This has led to the need for computing capacity to process the data close to where it is generated, at the edges of the network, in lieu of sending it to cloud datacenters. Edge […]

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