papers

Publications (74)

cs.LG2026

VIP-COP: Context Optimization for Tabular Foundation Models

Yilong Chen, Xueying Ding, Leman Akoglu

cs.SI2016

Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs

Emaad A. Manzoor, Sadegh Momeni, Venkat N. Venkatakrishnan +1

cs.LG2025

Mitra: Mixed Synthetic Priors for Enhancing Tabular Foundation Models

Xiyuan Zhang, Danielle C. Maddix, Junming Yin +11

cs.DB2015

Less is More: Building Selective Anomaly Ensembles

Shebuti Rayana, Leman Akoglu

cs.SI2017

LookOut on Time-Evolving Graphs: Succinctly Explaining Anomalies from Any Detector

Nikhil Gupta, Dhivya Eswaran, Neil Shah +2

cs.LG2022

A Comprehensive Survey on Graph Anomaly Detection with Deep Learning

Xiaoxiao Ma, Jia Wu, Shan Xue +5

cs.AI2026

Rethinking Evaluation for LLM Hallucination Detection: A Desiderata, A New RAG-based Benchmark, New Insights

Wenbo Chen, Veena Padmanabhan, Tootiya Giyahchi +2

cs.LG2026

MacrOData: New Benchmarks of Thousands of Datasets for Tabular Outlier Detection

Xueying Ding, Simon Klüttermann, Haomin Wen +2

cs.SI2017

Fast, Warped Graph Embedding: Unifying Framework and One-Click Algorithm

Siheng Chen, Sufeng Niu, Leman Akoglu +2

cs.LG2020

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

Jiong Zhu, Yujun Yan, Lingxiao Zhao +3

cs.DB2022

Anomaly Detection in Large Labeled Multi-Graph Databases

Hung T. Nguyen, Pierre J. Liang, Leman Akoglu

cs.LG2024

Outlier Detection Bias Busted: Understanding Sources of Algorithmic Bias through Data-centric Factors

Xueying Ding, Rui Xi, Leman Akoglu

cs.LG2024

Unified Discrete Diffusion for Categorical Data

Lingxiao Zhao, Xueying Ding, Lijun Yu +1

cs.SI2021

Detecting Changed-Hands Online Review Accounts

Geli Fei, Shuai Wang, Bing Liu +1

cs.SI2015

Where Graph Topology Matters: The Robust Subgraph Problem

Hau Chan, Shuchu Han, Leman Akoglu

cs.LG2021

Benefit-aware Early Prediction of Health Outcomes on Multivariate EEG Time Series

Shubhranshu Shekhar, Dhivya Eswaran, Bryan Hooi +3

cs.LG2021

Anomaly Mining -- Past, Present and Future

Leman Akoglu

cs.LG2015

Robust Semi-Supervised Classification for Multi-Relational Graphs

Junting Ye, Leman Akoglu

cs.LG2022

Toward Unsupervised Outlier Model Selection

Yue Zhao, Sean Zhang, Leman Akoglu

cs.LG2021

FairOD: Fairness-aware Outlier Detection

Shubhranshu Shekhar, Neil Shah, Leman Akoglu

cs.LG2022

Graph Anomaly Detection with Unsupervised GNNs

Lingxiao Zhao, Saurabh Sawlani, Arvind Srinivasan +1

cs.LG2021

Automating Outlier Detection via Meta-Learning

Yue Zhao, Ryan A. Rossi, Leman Akoglu

cs.SI2016

Temporal Opinion Spam Detection by Multivariate Indicative Signals

Junting Ye, Santhosh Kumar, Leman Akoglu

cs.DC2022

Sparx: Distributed Outlier Detection at Scale

Sean Zhang, Varun Ursekar, Leman Akoglu

cs.LG2022

D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments

Shuli Jiang, Robson Leonardo Ferreira Cordeiro, Leman Akoglu

cs.LG2023

ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach

Konstantinos Sotiropoulos, Lingxiao Zhao, Pierre Jinghong Liang +1

cs.SI2020

AutoAudit: Mining Accounting and Time-Evolving Graphs

Meng-Chieh Lee, Yue Zhao, Aluna Wang +4

cs.LG2025

Self-Tuning Self-Supervised Image Anomaly Detection

Jaemin Yoo, Lingxiao Zhao, Leman Akoglu

cs.LG2025

End-To-End Self-Tuning Self-Supervised Time Series Anomaly Detection

Boje Deforce, Meng-Chieh Lee, Bart Baesens +3

cs.SI2016

Scalable Anomaly Ranking of Attributed Neighborhoods

Bryan Perozzi, Leman Akoglu

cs.SI2024

On the Detection of Reviewer-Author Collusion Rings From Paper Bidding

Steven Jecmen, Nihar B. Shah, Fei Fang +1

cs.LG2024

Descriptive Kernel Convolution Network with Improved Random Walk Kernel

Meng-Chieh Lee, Lingxiao Zhao, Leman Akoglu

cs.LG2025

FoMo-0D: A Foundation Model for Zero-shot Tabular Outlier Detection

Yuchen Shen, Haomin Wen, Leman Akoglu

cs.DB2013

Want a Good Answer? Ask a Good Question First!

Yuan Yao, Hanghang Tong, Tao Xie +3

cs.LG2024

Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation

Lingxiao Zhao, Xueying Ding, Leman Akoglu

cs.CY2023

Unsupervised Machine Learning for Explainable Health Care Fraud Detection

Shubhranshu Shekhar, Jetson Leder-Luis, Leman Akoglu

cs.LG2024

Fast Unsupervised Deep Outlier Model Selection with Hypernetworks

Xueying Ding, Yue Zhao, Leman Akoglu

cs.SI2017

Ties That Bind - Characterizing Classes by Attributes and Social Ties

Aria Rezaei, Bryan Perozzi, Leman Akoglu

cs.NI2016

The Politics of Routing: Investigating the Relationship Between AS Connectivity and Internet Freedom

Rachee Singh, Hyungjoon Koo, Najmehalsadat Miramirkhani +3

physics.soc-ph2019

BuSCOPE : Fusing Individual & Aggregated Mobility Behavior for "Live" Smart City Services

Lakmal Meegahapola, Thivya Kandappu, Kasthuri Jayarajah +3

cs.LG2022

Hyperparameter Optimization for Unsupervised Outlier Detection

Yue Zhao, Leman Akoglu

cs.LG2022

Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution

Xueying Ding, Lingxiao Zhao, Leman Akoglu

cs.SI2022

Summarizing Labeled Multi-Graphs

Dimitris Berberidis, Pierre J. Liang, Leman Akoglu

cs.LG2021

C-AllOut: Catching & Calling Outliers by Type

Guilherme D. F. Silva, Leman Akoglu, Robson L. F. Cordeiro

stat.ML2019

Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection

Xiaoyi Gu, Leman Akoglu, Alessandro Rinaldo

cs.LG2023

From Explanation to Action: An End-to-End Human-in-the-loop Framework for Anomaly Reasoning and Management

Xueying Ding, Nikita Seleznev, Senthil Kumar +2

cs.LG2026

Toward Privileged Foundation Models:LUPI for Accelerated and Improved Learning

Xueying Ding, Leman Akoglu

cs.LG2021

A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice?

Martin Q. Ma, Yue Zhao, Xiaorong Zhang +1

cs.AI2016

BIRDNEST: Bayesian Inference for Ratings-Fraud Detection

Bryan Hooi, Neil Shah, Alex Beutel +5

cs.LG2021

Connecting Graph Convolutional Networks and Graph-Regularized PCA

Lingxiao Zhao, Leman Akoglu

cs.AI2026

Long-Horizon Plan Execution in Large Tool Spaces through Entropy-Guided Branching

Rongzhe Wei, Ge Shi, Min Cheng +5

cs.LG2021

Fast Attributed Graph Embedding via Density of States

Saurabh Sawlani, Lingxiao Zhao, Leman Akoglu

cs.SI2015

EdgeCentric: Anomaly Detection in Edge-Attributed Networks

Neil Shah, Alex Beutel, Bryan Hooi +5

cs.CL2025

Hierarchical Token Prepending: Enhancing Information Flow in Decoder-based LLM Embeddings

Xueying Ding, Xingyue Huang, Mingxuan Ju +5

cs.LG2019

Coverage-based Outlier Explanation

Yue Wu, Leman Akoglu, Ian Davidson

cs.LG2020

PairNorm: Tackling Oversmoothing in GNNs

Lingxiao Zhao, Leman Akoglu

cs.LG2026

Activation Steering for Synthetic Data Generation: The Role of Diversity in Downstream Safety Detection

Vijeta Deshpande, Tootiya Giyahchi, Veena Padmanabhan +2

cs.SI2014

Graph-based Anomaly Detection and Description: A Survey

Leman Akoglu, Hanghang Tong, Danai Koutra

cs.CL2026

Structured Prompt Optimization Meets Reinforcement Learning for Global and Local Interpretability over Complex Text

Tianyang Zhou, Wenbo Chen, Pierre Jinghong Liang +1

cs.LG2022

From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness

Lingxiao Zhao, Wei Jin, Leman Akoglu +1

cs.LG2025

CoBAD: Modeling Collective Behaviors for Human Mobility Anomaly Detection

Haomin Wen, Shurui Cao, Leman Akoglu

cs.LG2019

A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification

Xuan Wu, Lingxiao Zhao, Leman Akoglu

cs.LG2023

Data Augmentation is a Hyperparameter: Cherry-picked Self-Supervision for Unsupervised Anomaly Detection is Creating the Illusion of Success

Jaemin Yoo, Tiancheng Zhao, Leman Akoglu

cs.LG2021

SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection

Yue Zhao, Xiyang Hu, Cheng Cheng +11

cs.LG2018

Incorporating Privileged Information to Unsupervised Anomaly Detection

Shubhranshu Shekhar, Leman Akoglu

cs.LG2021

On Using Classification Datasets to Evaluate Graph-Level Outlier Detection: Peculiar Observations and New Insights

Lingxiao Zhao, Leman Akoglu

cs.LG2023

DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection

Jaemin Yoo, Yue Zhao, Lingxiao Zhao +1

cs.LG2016

Sequential Ensemble Learning for Outlier Detection: A Bias-Variance Perspective

Shebuti Rayana, Wen Zhong, Leman Akoglu

cs.LG2022

A Practical, Progressively-Expressive GNN

Lingxiao Zhao, Louis Härtel, Neil Shah +1

cs.LG2019

Continual Rare-Class Recognition with Emerging Novel Subclasses

Hung Nguyen, Xuejian Wang, Leman Akoglu

cs.LG2023

Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities

Leman Akoglu, Jaemin Yoo

cs.LG2018

Explaining Anomalies in Groups with Characterizing Subspace Rules

Meghanath Macha, Leman Akoglu

cs.LG2026

From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detection

Xueying Ding, Haomin Wen, Simon Klüttermann +1

cs.AI2025

Uncertainty-aware Human Mobility Modeling and Anomaly Detection

Haomin Wen, Shurui Cao, Zeeshan Rasheed +2