most citedAnomaly Detection in Bitcoin Network Using Unsupervised Learning Methods

68 citations · 131 across the 6 of their papers we have counts for

collaborators

7 papers

stat.ME2017★ 1 cited

Balancing Method for High Dimensional Causal Inference

Thai Pham

Causal inference has received great attention across different fields from economics, statistics, education, medicine, to machine learning. Within this area, inferring causal effec…

stat.ME2017

Estimating Average Treatment Effects: Supplementary Analyses and Remaining Challenges

Susan Athey, Guido Imbens, Thai Pham +1

There is a large literature on semiparametric estimation of average treatment effects under unconfounded treatment assignment in settings with a fixed number of covariates. More re…

cs.LG2016★ 4 cited

Low Latency Anomaly Detection and Bayesian Network Prediction of Anomaly Likelihood

Derek Farren, Thai Pham, Marco Alban-Hidalgo

We develop a supervised machine learning model that detects anomalies in systems in real time. Our model processes unbounded streams of data into time series which then form the ba…

cs.LG2016★ 2 cited

Unsupervised Learning For Effective User Engagement on Social Media

Thai Pham, Camelia Simoiu

In this paper, we investigate the effectiveness of unsupervised feature learning techniques in predicting user engagement on social media. Specifically, we compare two methods to p…

cs.SI2016★ 55 cited

Anomaly Detection in the Bitcoin System - A Network Perspective

Thai Pham, Steven Lee

The problem of anomaly detection has been studied for a long time, and many Network Analysis techniques have been proposed as solutions. Although some results appear to be quite pr…

cs.LG2016★ 68 cited

Anomaly Detection in Bitcoin Network Using Unsupervised Learning Methods

Thai Pham, Steven Lee

The problem of anomaly detection has been studied for a long time. In short, anomalies are abnormal or unlikely things. In financial networks, thieves and illegal activities are of…