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08/28/2023
RecRec: Algorithmic Recourse for Recommender Systems
Recommender systems play an essential role in the choices people make in...
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05/31/2023
Diffused Redundancy in Pre-trained Representations
Representations learned by pre-training a neural network on a large data...
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03/10/2023
Who's Thinking? A Push for Human-Centered Evaluation of LLMs using the XAI Playbook
Deployed artificial intelligence (AI) often impacts humans, and there is...
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12/14/2022
Tensions Between the Proxies of Human Values in AI
Motivated by mitigating potentially harmful impacts of technologies, the...
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12/09/2022
Networked Restless Bandits with Positive Externalities
Restless multi-armed bandits are often used to model budget-constrained ...
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11/29/2022
Robustness Disparities in Face Detection
Facial analysis systems have been deployed by large companies and critiq...
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11/09/2022
Interpretable Deep Reinforcement Learning for Green Security Games with Real-Time Information
Green Security Games with real-time information (GSG-I) add the real-tim...
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10/18/2022
On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition
Face recognition systems are deployed across the world by government age...
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10/05/2022
Equalizing Credit Opportunity in Algorithms: Aligning Algorithmic Fairness Research with U.S. Fair Lending Regulation
Credit is an essential component of financial wellbeing in America, and ...
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07/16/2022
Certified Neural Network Watermarks with Randomized Smoothing
Watermarking is a commonly used strategy to protect creators' rights to ...
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06/23/2022
Measuring Representational Robustness of Neural Networks Through Shared Invariances
A major challenge in studying robustness in deep learning is defining th...
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06/23/2022
On the Generalizability and Predictability of Recommender Systems
While other areas of machine learning have seen more and more automation...
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05/28/2022
Fair Labeled Clustering
Numerous algorithms have been produced for the fundamental problem of cl...
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05/27/2022
Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost
Clustering is a fundamental building block of modern statistical analysi...
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05/14/2022
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments
Visualizing optimization landscapes has led to many fundamental insights...
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02/22/2022
The Dichotomous Affiliate Stable Matching Problem: Approval-Based Matching with Applicant-Employer Relations
While the stable marriage problem and its variants model a vast range of...
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01/25/2022
Are Commercial Face Detection Models as Biased as Academic Models?
As facial recognition systems are deployed more widely, scholars and act...
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01/16/2022
Rawlsian Fairness in Online Bipartite Matching: Two-sided, Group, and Individual
Online bipartite-matching platforms are ubiquitous and find applications...
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12/06/2021
User-Driven Programming Support for Rapid Visualization Authoring in D3
D3 is arguably the most popular language for programming visualizations ...
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11/29/2021
Exploring Alignment of Representations with Human Perception
We argue that a valuable perspective on when a model learns good represe...
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10/27/2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization
Most state-of-the-art Graph Neural Networks (GNNs) can be defined as a f...
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10/15/2021
Comparing Human and Machine Bias in Face Recognition
Much recent research has uncovered and discussed serious concerns of bia...
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08/27/2021
Robustness Disparities in Commercial Face Detection
Facial detection and analysis systems have been deployed by large compan...
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08/10/2021
Matching Algorithms for Blood Donation
Global demand for donated blood far exceeds supply, and unmet need is gr...
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06/14/2021
Pitfalls of Explainable ML: An Industry Perspective
As machine learning (ML) systems take a more prominent and central role ...
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06/14/2021
Fair Clustering Under a Bounded Cost
Clustering is a fundamental unsupervised learning problem where a datase...
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06/09/2021
A New Notion of Individually Fair Clustering: α-Equitable k-Center
Clustering is a fundamental problem in unsupervised machine learning, an...
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06/07/2021
Amortized Generation of Sequential Counterfactual Explanations for Black-box Models
Explainable machine learning (ML) has gained traction in recent years du...
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06/06/2021
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning
The design of optimal auctions is a problem of interest in economics, ga...
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03/03/2021
Optimal Kidney Exchange with Immunosuppressants
Algorithms for exchange of kidneys is one of the key successful applicat...
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03/02/2021
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints
Metric clustering is fundamental in areas ranging from Combinatorial Opt...
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02/24/2021
Using Inverse Optimization to Learn Cost Functions in Generalized Nash Games
As demonstrated by Ratliff et al. (2014), inverse optimization can be us...
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02/12/2021
Technical Challenges for Training Fair Neural Networks
As machine learning algorithms have been widely deployed across applicat...
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12/23/2020
Noisy Labels Can Induce Good Representations
The current success of deep learning depends on large-scale labeled data...
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12/15/2020
Indecision Modeling
AI systems are often used to make or contribute to important decisions i...
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10/22/2020
Improving Policy-Constrained Kidney Exchange via Pre-Screening
In barter exchanges, participants swap goods with one another without ex...
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10/13/2020
ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning
The design of revenue-maximizing auctions with strong incentive guarante...
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09/24/2020
The Affiliate Matching Problem: On Labor Markets where Firms are Also Interested in the Placement of Previous Workers
In many labor markets, workers and firms are connected via affiliative r...
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07/14/2020
A Pairwise Fair and Community-preserving Approach to k-Center Clustering
Clustering is a foundational problem in machine learning with numerous a...
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07/07/2020
Kidney Exchange with Inhomogeneous Edge Existence Uncertainty
Motivated by kidney exchange, we study a stochastic cycle and chain pack...
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07/01/2020
Unifying Model Explainability and Robustness via Machine-Checkable Concepts
As deep neural networks (DNNs) get adopted in an ever-increasing number ...
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06/22/2020
Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks
Data poisoning and backdoor attacks manipulate training data in order to...
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06/19/2020
Probabilistic Fair Clustering
In clustering problems, a central decision-maker is given a complete met...
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06/17/2020
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning
Deep neural networks are being increasingly used in real world applicati...
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05/19/2020
Adapting a Kidney Exchange Algorithm to Align with Human Values
The efficient and fair allocation of limited resources is a classical pr...
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01/13/2020
Artificial Artificial Intelligence: Measuring Influence of AI 'Assessments' on Moral Decision-Making
Given AI's growing role in modeling and improving decision-making, how a...
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01/07/2020
Can an Algorithm be My Healthcare Proxy?
Planning for death is not a process in which everyone participates. Yet ...
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12/18/2019
Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms During High-Demand Hours
Rideshare platforms, when assigning requests to drivers, tend to maximiz...
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12/17/2019
Human Comprehension of Fairness in Machine Learning
Bias in machine learning has manifested injustice in several areas, such...
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12/09/2019