Search Results for author: Robert Shorten

Found 12 papers, 1 papers with code

Optimal Transport for Fairness: Archival Data Repair using Small Research Data Sets

no code implementations20 Mar 2024 Abigail Langbridge, Anthony Quinn, Robert Shorten

With the advent of the AI Act and other regulations, there is now an urgent need for algorithms that repair unfairness in training data.

Fairness

Fully Probabilistic Design for Optimal Transport

no code implementations19 Dec 2022 Sarah Boufelja Y., Anthony Quinn, Martin Corless, Robert Shorten

The goal of this paper is to introduce a new theoretical framework for Optimal Transport (OT), using the terminology and techniques of Fully Probabilistic Design (FPD).

Closed-Loop View of the Regulation of AI: Equal Impact across Repeated Interactions

no code implementations3 Sep 2022 Quan Zhou, Ramen Ghosh, Robert Shorten, Jakub Marecek

In a closed-loop view of the AI system and its users, the equal treatment concerns one pass through the loop.

Feedback control for distributed ledgers: An attack mitigation policy for DAG-based DLTs

no code implementations25 Apr 2022 Pietro Ferraro, Andreas Penzkofer, Christopher King, Robert Shorten

In this paper we present a feedback approach to the design of an attack mitigation policy for DAG-based Distributed Ledgers.

Reinforcement Learning with Algorithms from Probabilistic Structure Estimation

1 code implementation15 Mar 2021 Jonathan P. Epperlein, Roman Overko, Sergiy Zhuk, Christopher King, Djallel Bouneffouf, Andrew Cullen, Robert Shorten

In some cases, the environment is not influenced by the actions of the RL agent, in which case the problem can be modeled as a contextual multi-armed bandit and lightweight myopic algorithms can be employed.

reinforcement-learning Reinforcement Learning (RL)

I-nteract 2.0: A Cyber-Physical System to Design 3D Models using Mixed Reality Technologies and Deep Learning for Additive Manufacturing

no code implementations21 Oct 2020 Ammar Malik, Hugo Lhachemi, Robert Shorten

I-nteract is a cyber-physical system that enables real-time interaction with both virtual and real artifacts to design 3D models for additive manufacturing by leveraging on mixed reality technologies.

Mixed Reality

On Constant Distance Spacing Policies for Cooperative Adaptive Cruise Control

no code implementations23 Sep 2019 Kay Massow, Ilja Radusch, Robert Shorten

While constant distance headway (CDH) spacing policies provide superior potential to increase traffic capacity than CTH, a major drawback is a smaller safety margin at high velocities and string stability cannot be achieved using a one-vehicle look-ahead communication.

Spatial Positioning Token (SPToken) for Smart Mobility

no code implementations16 May 2019 Roman Overko, Rodrigo H. Ordonez-Hurtado, Sergiy Zhuk, Pietro Ferraro, Andrew Cullen, Robert Shorten

We introduce a permissioned distributed ledger technology (DLT) design for crowdsourced smart mobility applications.

Cryptography and Security

Bayesian Classifier for Route Prediction with Markov Chains

no code implementations31 Aug 2018 Jonathan P. Epperlein, Julien Monteil, Ming-ming Liu, Yingqi Gu, Sergiy Zhuk, Robert Shorten

We present here a general framework and a specific algorithm for predicting the destination, route, or more generally a pattern, of an ongoing journey, building on the recent work of [Y. Lassoued, J. Monteil, Y. Gu, G. Russo, R. Shorten, and M. Mevissen, "Hidden Markov model for route and destination prediction," in IEEE International Conference on Intelligent Transportation Systems, 2017].

Pricing Vehicle Sharing with Proximity Information

no code implementations25 Jan 2016 Jakub Marecek, Robert Shorten, Jia Yuan Yu

For vehicle sharing schemes, where drop-off positions are not fixed, we propose a pricing scheme, where the price depends in part on the distance between where a vehicle is being dropped off and where the closest shared vehicle is parked.

r-Extreme Signalling for Congestion Control

no code implementations9 Apr 2014 Jakub Marecek, Robert Shorten, Jia Yuan Yu

A central authority has up-to-date knowledge of the congestion across all resources and uses randomisation to provide a scalar or an interval for each resource at each time.

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