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10/16/2022
Loss Minimization through the Lens of Outcome Indistinguishability
We present a new perspective on loss minimization and the recent notion ...
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02/28/2022
KL Divergence Estimation with Multi-group Attribution
Estimating the Kullback-Leibler (KL) divergence between two distribution...
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09/11/2021
Omnipredictors
Loss minimization is a dominant paradigm in machine learning, where a pr...
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03/10/2021
Multicalibrated Partitions for Importance Weights
The ratio between the probability that two distributions R and P give to...
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06/22/2020
Overlook: Differentially Private Exploratory Visualization for Big Data
Data exploration systems that provide differential privacy must manage a...
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12/08/2019
PIDForest: Anomaly Detection via Partial Identification
We consider the problem of detecting anomalies in a large dataset. We pr...
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11/18/2019
Finding Skewed Subcubes Under a Distribution
Say that we are given samples from a distribution ψ over an n-dimensiona...
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07/10/2019
Hillview: A trillion-cell spreadsheet for big data
Hillview is a distributed spreadsheet for browsing very large datasets t...
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06/06/2018
Another Proof of Cuckoo hashing with New Variants
We show a new proof for the load of obtained by a Cuckoo Hashing data st...
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04/09/2018