1.4k citations · 5k across the 110 of their papers we have counts for
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Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes
Nikhil Garg, Londa Schiebinger, Dan Jurafsky +1
Word embeddings use vectors to represent words such that the geometry between vectors captures semantic relationship between the words. In this paper, we develop a framework to dem…
NeuralFDR: Learning Discovery Thresholds from Hypothesis Features
Fei Xia, Martin J. Zhang, James Zou +1
As datasets grow richer, an important challenge is to leverage the full features in the data to maximize the number of useful discoveries while controlling for false positives. We…
The Effects of Memory Replay in Reinforcement Learning
Ruishan Liu, James Zou
Experience replay is a key technique behind many recent advances in deep reinforcement learning. Allowing the agent to learn from earlier memories can speed up learning and break u…
Interpretation of Neural Networks is Fragile
Amirata Ghorbani, Abubakar Abid, James Zou
In order for machine learning to be deployed and trusted in many applications, it is crucial to be able to reliably explain why the machine learning algorithm makes certain predict…
Contrastive Principal Component Analysis
Abubakar Abid, Martin J. Zhang, Vivek K. Bagaria +1
We present a new technique called contrastive principal component analysis (cPCA) that is designed to discover low-dimensional structure that is unique to a dataset, or enriched in…
Why Adaptively Collected Data Have Negative Bias and How to Correct for It
Xinkun Nie, Xiaoying Tian, Jonathan Taylor +1
From scientific experiments to online A/B testing, the previously observed data often affects how future experiments are performed, which in turn affects which data will be collect…
Estimating the unseen from multiple populations
Aditi Raghunathan, Greg Valiant, James Zou
Given samples from a distribution, how many new elements should we expect to find if we continue sampling this distribution? This is an important and actively studied problem, with…
Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context
Shyam Upadhyay, Kai-Wei Chang, Matt Taddy +2
Word embeddings, which represent a word as a point in a vector space, have become ubiquitous to several NLP tasks. A recent line of work uses bilingual (two languages) corpora to l…
Linear Regression with Shuffled Labels
Abubakar Abid, Ada Poon, James Zou
Is it possible to perform linear regression on datasets whose labels are shuffled with respect to the inputs? We explore this question by proposing several estimators that recover…