Serena Wang | DeepAI

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Featured Co-authors

Michael I. Jordan
283 publications
Nathan Srebro
96 publications
Benjamin Recht
63 publications
Karthik Sridharan
40 publications
Aditya Krishna Menon
35 publications
Yixin Wang
32 publications
Sara Hooker
28 publications
Heinrich Jiang
28 publications
Peng Ding
26 publications
Blake Woodworth
24 publications
Harikrishna Narasimhan
22 publications

∙ 09/08/2022

Lost in Translation: Reimagining the Machine Learning Life Cycle in Education

Machine learning (ML) techniques are increasingly prevalent in education...

0 Lydia T. Liu, et al. ∙

∙ 06/13/2022

Robust Distillation for Worst-class Performance

Knowledge distillation has proven to be an effective technique in improv...

12 Serena Wang, et al. ∙

∙ 06/30/2021

Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence

Variational Inference (VI) is a popular alternative to asymptotically ex...

2 Ghassen Jerfel, et al. ∙

∙ 03/30/2021

Multi-Source Causal Inference Using Control Variates

While many areas of machine learning have benefited from the increasing ...

16 Wenshuo Guo, et al. ∙

∙ 02/09/2021

Regularization Strategies for Quantile Regression

We investigate different methods for regularizing quantile regression wh...

0 Taman Narayan, et al. ∙

∙ 07/10/2020

Finding Equilibrium in Multi-Agent Games with Payoff Uncertainty

We study the problem of finding equilibrium strategies in multi-agent ga...

0 Wenshuo Guo, et al. ∙

∙ 02/21/2020

Robust Optimization for Fairness with Noisy Protected Groups

Many existing fairness criteria for machine learning involve equalizing ...

6 Serena Wang, et al. ∙

∙ 01/31/2020

Deontological Ethics By Monotonicity Shape Constraints

We demonstrate how easy it is for modern machine-learned systems to viol...

10 Serena Wang, et al. ∙

∙ 06/12/2019

Pairwise Fairness for Ranking and Regression

We present pairwise metrics of fairness for ranking and regression model...

0 Harikrishna Narasimhan, et al. ∙

∙ 09/11/2018

Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals

We show that many machine learning goals, such as improved fairness metr...

0 Andrew Cotter, et al. ∙

∙ 06/29/2018

Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints

Classifiers can be trained with data-dependent constraints to satisfy fa...

0 Andrew Cotter, et al. ∙

∙ 06/28/2018

Proxy Fairness

We consider the problem of improving fairness when one lacks access to a...

0 Maya Gupta, et al. ∙

∙ 06/28/2018

Quit When You Can: Efficient Evaluation of Ensembles with Ordering Optimization

Given a classifier ensemble and a set of examples to be classified, many...

0 Serena Wang, et al. ∙

∙ 05/31/2018

Interpretable Set Functions

We propose learning flexible but interpretable functions that aggregate ...

0 Andrew Cotter, et al. ∙

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