Krishnaram Kenthapadi

research

∙ 05/31/2023

Designing Closed-Loop Models for Task Allocation

Automatically assigning tasks to people is challenging because human per...

0 Vijay Keswani, et al. ∙

research

∙ 07/06/2022

Towards the Use of Saliency Maps for Explaining Low-Quality Electrocardiograms to End Users

When using medical images for diagnosis, either by clinicians or artific...

15 Ana Lucic, et al. ∙

research

∙ 06/25/2022

Visual Auditor: Interactive Visualization for Detection and Summarization of Model Biases

As machine learning (ML) systems become increasingly widespread, it is n...

0 David Munechika, et al. ∙

research

∙ 06/06/2022

A Human-Centric Take on Model Monitoring

Predictive models are increasingly used to make various consequential de...

0 Murtuza N. Shergadwala, et al. ∙

research

∙ 04/09/2022

Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks

We show that deep neural networks that satisfy demographic parity do so ...

0 Michael Lohaus, et al. ∙

research

∙ 03/21/2022

Diverse Counterfactual Explanations for Anomaly Detection in Time Series

Data-driven methods that detect anomalies in times series data are ubiqu...

0 Déborah Sulem, et al. ∙

research

∙ 02/17/2022

Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness

Much of machine learning research focuses on predictive accuracy: given ...

0 Kate Donahue, et al. ∙

research

∙ 02/09/2022

Designing Closed Human-in-the-loop Deferral Pipelines

In hybrid human-machine deferral frameworks, a classifier can defer unce...

0 Vijay Keswani, et al. ∙

research

∙ 12/23/2021

More Than Words: Towards Better Quality Interpretations of Text Classifiers

The large size and complex decision mechanisms of state-of-the-art text ...

0 Muhammad Bilal Zafar, et al. ∙

research

∙ 11/26/2021

Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models

With the increasing adoption of machine learning (ML) models and systems...

0 David Nigenda, et al. ∙

research

∙ 09/07/2021

Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud

Understanding the predictions made by machine learning (ML) models and t...

30 Michaela Hardt, et al. ∙

research

∙ 07/09/2021

Multiaccurate Proxies for Downstream Fairness

We study the problem of training a model that must obey demographic fair...

1 Emily Diana, et al. ∙

research

∙ 06/08/2021

On the Lack of Robust Interpretability of Neural Text Classifiers

With the ever-increasing complexity of neural language models, practitio...

0 Muhammad Bilal Zafar, et al. ∙

research

∙ 05/14/2021

On Measuring the Diversity of Organizational Networks

The interaction patterns of employees in social and professional network...

0 Zeinab S. Jalali, et al. ∙

research

∙ 05/07/2021

Pairwise Fairness for Ordinal Regression

We initiate the study of fairness for ordinal regression, or ordinal cla...

0 Matthäus Kleindessner, et al. ∙

research

∙ 03/11/2021

Differentially Private Query Release Through Adaptive Projection

We propose, implement, and evaluate a new algorithm for releasing answer...

9 Sergul Aydore, et al. ∙

research

∙ 02/25/2021

Towards Unbiased and Accurate Deferral to Multiple Experts

Machine learning models are often implemented in cohort with humans in t...

0 Vijay Keswani, et al. ∙

research

∙ 02/11/2021

Defuse: Harnessing Unrestricted Adversarial Examples for Debugging Models Beyond Test Accuracy

We typically compute aggregate statistics on held-out test data to asses...

26 Dylan Slack, et al. ∙

research

∙ 12/15/2020

Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization

Tuning complex machine learning systems is challenging. Machine learning...

0 Valerio Perrone, et al. ∙

research

∙ 11/05/2020

Convergent Algorithms for (Relaxed) Minimax Fairness

We consider a recently introduced framework in which fairness is measure...

7 Emily Diana, et al. ∙

research

∙ 08/14/2020

LiFT: A Scalable Framework for Measuring Fairness in ML Applications

Many internet applications are powered by machine learned models, which ...

23 Sriram Vasudevan, et al. ∙

research

∙ 07/30/2020

Fairness-Aware Online Personalization

Decision making in crucial applications such as lending, hiring, and col...

0 G. Roshan Lal, et al. ∙

research

∙ 07/10/2020

Evaluating Fairness Using Permutation Tests

Machine learning models are central to people's lives and impact society...

0 Cyrus DiCiccio, et al. ∙

research

∙ 06/09/2020

Fair Bayesian Optimization

Given the increasing importance of machine learning (ML) in our lives, a...

31 Valerio Perrone, et al. ∙

research

∙ 04/30/2019

Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search

Recently, policymakers, regulators, and advocates have raised awareness ...

0 Sahin Cem Geyik, et al. ∙

research

∙ 04/10/2019

What's in a Name? Reducing Bias in Bios without Access to Protected Attributes

There is a growing body of work that proposes methods for mitigating bia...

12 Alexey Romanov, et al. ∙

research

∙ 01/27/2019

Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting

We present a large-scale study of gender bias in occupation classificati...

36 Maria De-Arteaga, et al. ∙

research

∙ 09/20/2018

PriPeARL: A Framework for Privacy-Preserving Analytics and Reporting at LinkedIn

Preserving privacy of users is a key requirement of web-scale analytics ...

0 Krishnaram Kenthapadi, et al. ∙

research

∙ 09/18/2018

Talent Search and Recommendation Systems at LinkedIn: Practical Challenges and Lessons Learned

LinkedIn Talent Solutions business contributes to around 65 annual reven...

0 Sahin Cem Geyik, et al. ∙

research

∙ 09/17/2018

Towards Deep and Representation Learning for Talent Search at LinkedIn

Talent search and recommendation systems at LinkedIn strive to match the...

0 Rohan Ramanath, et al. ∙

research

∙ 03/29/2017

Bringing Salary Transparency to the World: Computing Robust Compensation Insights via LinkedIn Salary

The recently launched LinkedIn Salary product has been designed with the...

0 Krishnaram Kenthapadi, et al. ∙

Krishnaram Kenthapadi

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