116 citations · 798 across the 53 of their papers we have counts for
12 papers · 2 filters
Suspicious Massive Registration Detection via Dynamic Heterogeneous Graph Neural Networks
Susie Xi Rao, Shuai Zhang, Zhichao Han +6
Massive account registration has raised concerns on risk management in e-commerce companies, especially when registration increases rapidly within a short time frame. To monitor th…
Efficient Automatic CASH via Rising Bandits
Yang Li, Jiawei Jiang, Jinyang Gao +3
The Combined Algorithm Selection and Hyperparameter optimization (CASH) is one of the most fundamental problems in Automatic Machine Learning (AutoML). The existing Bayesian optimi…
MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements
Yang Li, Yu Shen, Jiawei Jiang +3
Hyperparameter optimization (HPO) is a fundamental problem in automatic machine learning (AutoML). However, due to the expensive evaluation cost of models (e.g., training deep lear…
xFraud: Explainable Fraud Transaction Detection
Susie Xi Rao, Shuai Zhang, Zhichao Han +6
At online retail platforms, it is crucial to actively detect the risks of transactions to improve customer experience and minimize financial loss. In this work, we propose xFraud,…
On Convergence of Nearest Neighbor Classifiers over Feature Transformations
Luka Rimanic, Cedric Renggli, Bo Li +1
The k-Nearest Neighbors (kNN) classifier is a fundamental non-parametric machine learning algorithm. However, it is well known that it suffers from the curse of dimensionality, whi…
Online Active Model Selection for Pre-trained Classifiers
Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlaš +3
Given pre-trained classifiers and a stream of unlabeled data examples, how can we actively decide when to query a label so that we can distinguish the best model from the rest…