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Found 10 papers, 0 papers with code
Driver Fatigue Prediction using Randomly Activated Neural Networks for Smart Ridesharing Platforms
Drivers in ridesharing platforms exhibit cognitive atrophy and fatigue as they accept ride offers along the day, which can have a significant impact on the overall efficiency of the ridesharing platform.
Convolutional Spiking Neural Networks for Detecting Anticipatory Brain Potentials Using Electroencephalogram
Performance of the CSNN was comparable to the CNN in an ablation study using a subset of EEG channels that localized SCPs.
On Learning and Enforcing Latent Assessment Models using Binary Feedback from Human Auditors Regarding Black-Box Classifiers
Algorithmic fairness literature presents numerous mathematical notions and metrics, and also points to a tradeoff between them while satisficing some or all of them simultaneously.
Online-Learning Deep Neuro-Adaptive Dynamic Inversion Controller for Model Free Control
Adaptive methods are popular within the control literature due to the flexibility and forgiveness they offer in the area of modelling.
Strategic Mitigation of Agent Inattention in Drivers with Open-Quantum Cognition Models
Therefore, in an attempt to improve the persuasive effectiveness of driver-assist systems, we develop a novel strategic and personalized driver-assist system which adapts to the driver's mental state and choice behavior.
Non-Comparative Fairness for Human-Auditing and Its Relation to Traditional Fairness Notions
We show that any MLS can be deemed fair from the perspective of comparative fairness (be it in terms of individual fairness, statistical parity, equal opportunity or calibration) if it is non-comparatively fair with respect to a fair auditor.
On the Design of Strategic Task Recommendations for Sustainable Crowdsourcing-Based Content Moderation
Crowdsourcing-based content moderation is a platform that hosts content moderation tasks for crowd workers to review user submissions (e. g. text, images and videos) and make decisions regarding the admissibility of the posted content, along with a gamut of other tasks such as image labeling and speech-to-text conversion.
On the Identification of Fair Auditors to Evaluate Recommender Systems based on a Novel Non-Comparative Fairness Notion
We show that the proposed fairness notion also provides guarantees in terms of comparative fairness notions by proving that any system can be deemed fair from the perspective of comparative fairness (e. g. individual fairness and statistical parity) if it is non-comparatively fair with respect to an auditor who has been deemed fair with respect to the same fairness notions.
Framing Effects on Strategic Information Design under Receiver Distrust and Unknown State
Furthermore, given that the receiver does not trust the sender, we also assume that the receiver updates its prior in a non-Bayesian manner.
On Estimating Multi-Attribute Choice Preferences using Private Signals and Matrix Factorization
Therefore, we propose a simple generative choice model where agents are assumed to generate the choice probabilities based on latent factor matrices that capture their choice evaluation across multiple attributes.
