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09/21/2023
Simulation-to-reality UAV Fault Diagnosis in windy environments
Monitoring propeller failures is vital to maintain the safe and reliable...
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02/16/2023
Difference-based Deep Convolutional Neural Network for Simulation-to-reality UAV Fault Diagnosis
Identifying the fault in propellers is important to keep quadrotors oper...
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02/09/2023
Simulation-to-reality UAV Fault Diagnosis with Deep Learning
Accurate diagnosis of propeller faults is crucial for ensuring the safe ...
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07/29/2022
Exponential canonical correlation analysis with orthogonal variation
Canonical correlation analysis (CCA) is a standard tool for studying ass...
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06/22/2022
Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI
Recent years have seen a surge of interest in the field of explainable A...
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05/11/2022
De-biasing "bias" measurement
When a model's performance differs across socially or culturally relevan...
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04/25/2022
Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation
Despite impressive performance in many benchmark datasets, AI models can...
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09/24/2021
AI Explainability 360: Impact and Design
As artificial intelligence and machine learning algorithms become increa...
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06/02/2021
Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI
In this paper, we describe an open source Python toolkit named Uncertain...
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05/08/2021
D2S: Document-to-Slide Generation Via Query-Based Text Summarization
Presentations are critical for communication in all areas of our lives, ...
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04/09/2021
Model LineUpper: Supporting Interactive Model Comparison at Multiple Levels for AutoML
Automated Machine Learning (AutoML) is a rapidly growing set of technolo...
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03/22/2021
Enhancing the Generalization Performance and Speed Up Training for DRL-based Mapless Navigation
Training an agent to navigate with DRL is data-hungry, which requires mi...
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01/07/2021
How Much Automation Does a Data Scientist Want?
Data science and machine learning (DS/ML) are at the heart of the recent...
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11/15/2020
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty
Transparency of algorithmic systems entails exposing system properties t...
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10/20/2020
Learn to Navigate Maplessly with Varied LiDAR Configurations: A Support Point Based Approach
Deep reinforcement learning (DRL) demonstrates great potential in maples...
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10/15/2020
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making
Several strands of research have aimed to bridge the gap between artific...
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09/06/2020
Active Learning++: Incorporating Annotator's Rationale using Local Model Explanation
We propose a new active learning (AL) framework, Active Learning++, whic...
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04/04/2020
Measuring Social Biases of Crowd Workers using Counterfactual Queries
Social biases based on gender, race, etc. have been shown to pollute mac...
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03/12/2020
Model Agnostic Multilevel Explanations
In recent years, post-hoc local instance-level and global dataset-level ...
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03/02/2020
Business (mis)Use Cases of Generative AI
Generative AI is a class of machine learning technology that learns to g...
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02/15/2020
Map-less Navigation: A Single DRL-based Controller for Robots with Varied Dimensions
Deep reinforcement learning (DRL) has shown great potential in training ...
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02/05/2020
Joint Optimization of AI Fairness and Utility: A Human-Centered Approach
Today, AI is increasingly being used in many high-stakes decision-making...
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01/24/2020
Explainable Active Learning (XAL): An Empirical Study of How Local Explanations Impact Annotator Experience
Active Learning (AL) is a human-in-the-loop Machine Learning paradigm fa...
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01/13/2020
Consumer-Driven Explanations for Machine Learning Decisions: An Empirical Study of Robustness
Many proposed methods for explaining machine learning predictions are in...
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01/07/2020
Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making
Today, AI is being increasingly used to help human experts make decision...
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09/06/2019
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
As artificial intelligence and machine learning algorithms make further ...
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01/23/2019
Explaining Models: An Empirical Study of How Explanations Impact Fairness Judgment
Ensuring fairness of machine learning systems is a human-in-the-loop pro...
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12/14/2018
Bootstrapping Conversational Agents With Weak Supervision
Many conversational agents in the market today follow a standard bot dev...
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11/20/2018
Joint association and classification analysis of multi-view data
Multi-view data, that is matched sets of measurements on the same subjec...
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10/03/2018
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
Fairness is an increasingly important concern as machine learning models...
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09/11/2018
Danger-aware Weighted Advantage Composition of Deep Reinforcement Learning for Robot Navigation
Self-navigation, referring to automatically reaching the goal while avoi...
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10/04/2017
Combining absolute and relative pointing for fast and accurate distant interaction
Traditional relative pointing devices such as mice and trackpads are uns...
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10/04/2017
