Daniel B. Neill | DeepAI

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∙ 06/22/2023

Auditing Predictive Models for Intersectional Biases

Predictive models that satisfy group fairness criteria in aggregate for ...

0 Kate S. Boxer, et al. ∙

∙ 06/19/2023

Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness

In this paper, we develop a new criterion, "insufficiently justified dis...

0 Neil Menghani, et al. ∙

∙ 02/13/2023

Provable Detection of Propagating Sampling Bias in Prediction Models

With an increased focus on incorporating fairness in machine learning mo...

0 Pavan Ravishankar, et al. ∙

∙ 06/26/2022

Calibrated Nonparametric Scan Statistics for Anomalous Pattern Detection in Graphs

We propose a new approach, the calibrated nonparametric scan statistic (...

0 Chunpai Wang, et al. ∙

∙ 11/19/2021

Positional Encoder Graph Neural Networks for Geographic Data

Graph neural networks (GNNs) provide a powerful and scalable solution fo...

0 Konstantin Klemmer, et al. ∙

∙ 09/30/2021

SPATE-GAN: Improved Generative Modeling of Dynamic Spatio-Temporal Patterns with an Autoregressive Embedding Loss

From ecology to atmospheric sciences, many academic disciplines deal wit...

3 Konstantin Klemmer, et al. ∙

∙ 11/11/2020

Policing Chronic and Temporary Hot Spots of Violent Crime: A Controlled Field Experiment

Hot-spot-based policing programs aim to deter crime through increased pr...

0 Dylan J Fitzpatrick, et al. ∙

∙ 06/18/2020

SXL: Spatially explicit learning of geographic processes with auxiliary tasks

From earth system sciences to climate modeling and ecology, many of the ...

0 Konstantin Klemmer, et al. ∙

∙ 11/09/2018

Modeling Rape Reporting Delays Using Spatial, Temporal and Social Features

We present a novel approach to estimate the delay observed between the o...

0 Konstantin Klemmer, et al. ∙

∙ 10/28/2018

Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction

Identifying changes in model parameters is fundamental in machine learni...

8 William Herlands, et al. ∙

∙ 04/04/2018

Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data

Identifying anomalous patterns in real-world data is essential for under...

0 William Herlands, et al. ∙

∙ 03/24/2018

Efficient Discovery of Heterogeneous Treatment Effects in Randomized Experiments via Anomalous Pattern Detection

The randomized experiment is an important tool for inferring the causal ...

0 Edward McFowland III, et al. ∙

∙ 10/06/2017

Machine Learning for Drug Overdose Surveillance

We describe two recently proposed machine learning approaches for discov...

0 Daniel B. Neill, et al. ∙

∙ 01/05/2017

Graph Structure Learning from Unlabeled Data for Event Detection

Processes such as disease propagation and information diffusion often sp...

0 Sriram Somanchi, et al. ∙

∙ 02/13/2016

Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams

Early detection and precise characterization of emerging topics in text ...

0 Abhinav Maurya, et al. ∙

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