449 citations · 620 across the 23 of their papers we have counts for
24 papers
Explaining the Success of Nearest Neighbor Methods in Prediction
George H. Chen, Devavrat Shah
Many modern methods for prediction leverage nearest neighbor search to find past training examples most similar to a test example, an idea that dates back in text to at least the 1…
Neurological Prognostication of Post-Cardiac-Arrest Coma Patients Using EEG Data: A Dynamic Survival Analysis Framework with Competing Risks
Xiaobin Shen, Jonathan Elmer, George H. Chen
Patients resuscitated from cardiac arrest who enter a coma are at high risk of death. Forecasting neurological outcomes of these patients (the task of neurological prognostication)…
Improving Fairness in Deepfake Detection
Yan Ju, Shu Hu, Shan Jia +2
Despite the development of effective deepfake detectors in recent years, recent studies have demonstrated that biases in the data used to train these detectors can lead to disparit…
A General Framework for Visualizing Embedding Spaces of Neural Survival Analysis Models Based on Angular Information
George H. Chen
We propose a general framework for visualizing any intermediate embedding representation used by any neural survival analysis model. Our framework is based on so-called anchor dire…
Distributionally Robust Survival Analysis: A Novel Fairness Loss Without Demographics
Shu Hu, George H. Chen
We propose a general approach for training survival analysis models that minimizes a worst-case error across all subpopulations that are large enough (occurring with at least a use…
Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee
George H. Chen
Kernel survival analysis models estimate individual survival distributions with the help of a kernel function, which measures the similarity between any two data points. Such a ker…
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs
Kay Liu, Yingtong Dou, Yue Zhao +12
Detecting which nodes in graphs are outliers is a relatively new machine learning task with numerous applications. Despite the proliferation of algorithms developed in recent years…
PyGOD: A Python Library for Graph Outlier Detection
Kay Liu, Yingtong Dou, Xueying Ding +5
PyGOD is an open-source Python library for detecting outliers in graph data. As the first comprehensive library of its kind, PyGOD supports a wide array of leading graph-based meth…
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions
Zheng Li, Yue Zhao, Xiyang Hu +3
Outlier detection refers to the identification of data points that deviate from a general data distribution. Existing unsupervised approaches often suffer from high computational c…
TOD: GPU-accelerated Outlier Detection via Tensor Operations
Yue Zhao, George H. Chen, Zhihao Jia
Outlier detection (OD) is a key learning task for finding rare and deviant data samples, with many time-critical applications such as fraud detection and intrusion detection. In th…
Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction Intervals
George H. Chen
Kernel survival analysis methods predict subject-specific survival curves and times using information about which training subjects are most similar to a test subject. These most s…
Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate
George H. Chen, Linhong Li, Ren Zuo +2
We present a neural network framework for learning a survival model to predict a time-to-event outcome while simultaneously learning a topic model that reveals feature relationship…
Predicting Mortality Risk in Viral and Unspecified Pneumonia to Assist Clinicians with COVID-19 ECMO Planning
Helen Zhou, Cheng Cheng, Zachary C. Lipton +2
Respiratory complications due to coronavirus disease COVID-19 have claimed tens of thousands of lives in 2020. Many cases of COVID-19 escalate from Severe Acute Respiratory Syndrom…
Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online
Emaad Manzoor, George H. Chen, Dokyun Lee +1
Deliberation among individuals online plays a key role in shaping the opinions that drive votes, purchases, donations and other critical offline behavior. Yet, the determinants of…
Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption
Wei Ma, George H. Chen
Matrix completion is often applied to data with entries missing not at random (MNAR). For example, consider a recommendation system where users tend to only reveal ratings for item…
Truck Traffic Monitoring with Satellite Images
Lynn H. Kaack, George H. Chen, M. Granger Morgan
The road freight sector is responsible for a large and growing share of greenhouse gas emissions, but reliable data on the amount of freight that is moved on roads in many parts of…
Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates
George H. Chen
We establish the first nonasymptotic error bounds for Kaplan-Meier-based nearest neighbor and kernel survival probability estimators where feature vectors reside in metric spaces.…
An Interpretable Produce Price Forecasting System for Small and Marginal Farmers in India using Collaborative Filtering and Adaptive Nearest Neighbors
Wei Ma, Kendall Nowocin, Niraj Marathe +1
Small and marginal farmers, who account for over 80% of India's agricultural population, often sell their harvest at low, unfavorable prices before spoilage. These farmers often la…
Survival-Supervised Topic Modeling with Anchor Words: Characterizing Pancreatitis Outcomes
George H. Chen, Jeremy C. Weiss
We introduce a new approach for topic modeling that is supervised by survival analysis. Specifically, we build on recent work on unsupervised topic modeling with so-called anchor w…
Toward Reducing Crop Spoilage and Increasing Small Farmer Profits in India: a Simultaneous Hardware and Software Solution
George H. Chen, Kendall Nowocin, Niraj Marathe
India's agricultural system has been facing a severe problem of crop wastage. A key contributing factor to this problem is that many small farmers lack access to reliable cold stor…
A Latent Source Model for Patch-Based Image Segmentation
George Chen, Devavrat Shah, Polina Golland
Despite the popularity and empirical success of patch-based nearest-neighbor and weighted majority voting approaches to medical image segmentation, there has been no theoretical de…
A Latent Source Model for Online Collaborative Filtering
Guy Bresler, George H. Chen, Devavrat Shah
Despite the prevalence of collaborative filtering in recommendation systems, there has been little theoretical development on why and how well it works, especially in the "online"…
Sparse Projections of Medical Images onto Manifolds
George H. Chen, Christian Wachinger, Polina Golland
Manifold learning has been successfully applied to a variety of medical imaging problems. Its use in real-time applications requires fast projection onto the low-dimensional space.…
A Latent Source Model for Nonparametric Time Series Classification
George H. Chen, Stanislav Nikolov, Devavrat Shah
For classifying time series, a nearest-neighbor approach is widely used in practice with performance often competitive with or better than more elaborate methods such as neural net…