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05/30/2023
Disentangling and Operationalizing AI Fairness at LinkedIn
Operationalizing AI fairness at LinkedIn's scale is challenging not only...
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03/15/2023
Automated Interactive Domain-Specific Conversational Agents that Understand Human Dialogs
Achieving human-like communication with machines remains a classic, chal...
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02/03/2023
An Operational Perspective to Fairness Interventions: Where and How to Intervene
As AI-based decision systems proliferate, their successful operationaliz...
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08/24/2022
Pushing the limits of fairness impossibility: Who's the fairest of them all?
The impossibility theorem of fairness is a foundational result in the al...
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04/12/2022
Detection and Mitigation of Algorithmic Bias via Predictive Rate Parity
Recently, numerous studies have demonstrated the presence of bias in mac...
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03/30/2022
Long-term Dynamics of Fairness Intervention in Connection Recommender Systems
Recommender system fairness has been studied from the perspectives of a ...
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02/10/2022
Heterogeneous Calibration: A post-hoc model-agnostic framework for improved generalization
We introduce the notion of heterogeneous calibration that applies a post...
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02/04/2022
Generalized Causal Tree for Uplift Modeling
Uplift modeling is crucial in various applications ranging from marketin...
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12/21/2021
An ASP-based Approach to Answering Natural Language Questions for Texts
An approach based on answer set programming (ASP) is proposed in this pa...
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10/17/2021
AUTO-DISCERN: Autonomous Driving Using Common Sense Reasoning
Driving an automobile involves the tasks of observing surroundings, then...
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10/11/2021
CASPR: A Commonsense Reasoning-based Conversational Socialbot
We report on the design and development of the CASPR system, a socialbot...
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09/17/2021
DiscASP: A Graph-based ASP System for Finding Relevant Consistent Concepts with Applications to Conversational Socialbots
We consider the problem of finding relevant consistent concepts in a con...
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09/10/2021
Knowledge-Assisted Reasoning of Model-Augmented System Requirements with Event Calculus and Goal-Directed Answer Set Programming
We consider requirements for cyber-physical systems represented in const...
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03/09/2021
Efficient Algorithms for Global Inference in Internet Marketplaces
Matching demand to supply in internet marketplaces (e-commerce, ride-sha...
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01/27/2021
Knowledge-driven Natural Language Understanding of English Text and its Applications
Understanding the meaning of a text is a fundamental challenge of natura...
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09/22/2020
SQuARE: Semantics-based Question Answering and Reasoning Engine
Understanding the meaning of a text is a fundamental challenge of natura...
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07/10/2020
Evaluating Fairness Using Permutation Tests
Machine learning models are central to people's lives and impact society...
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06/23/2020
A Framework for Fairness in Two-Sided Marketplaces
Many interesting problems in the Internet industry can be framed as a tw...
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06/19/2020
Scalable Assessment and Mitigation Strategies for Fairness in Rankings
Motivated by industrial-scale applications, we consider two specific are...
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09/18/2019
Conversational AI : Open Domain Question Answering and Commonsense Reasoning
Our research is focused on making a human-like question answering system...
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06/08/2019
Optimal Convergence for Stochastic Optimization with Multiple Expectation Constraints
In this paper, we focus on the problem of stochastic optimization where ...
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01/29/2019
Personalization and Optimization of Decision Parameters via Heterogenous Causal Effects
Randomized experimentation (also known as A/B testing or bucket testing)...
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01/29/2019
A/B Testing in Dense Large-Scale Networks: Design and Inference
Design of experiments and estimation of treatment effects in large-scale...
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10/02/2017
Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences
We consider the problem of solving a large-scale Quadratically Constrain...
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05/18/2017
Analysis of Thompson Sampling for Gaussian Process Optimization in the Bandit Setting
We consider the global optimization of a function over a continuous doma...
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02/13/2016
Constrained Multi-Slot Optimization for Ranking Recommendations
Ranking items to be recommended to users is one of the main problems in ...
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02/09/2016
Large scale multi-objective optimization: Theoretical and practical challenges
Multi-objective optimization (MOO) is a well-studied problem for several...
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09/09/2012
