Neil Shah

Orcid: 0000-0003-3261-8430

According to our database1, Neil Shah authored at least 131 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

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On csauthors.net:

Bibliography

2024
Guest Editorial: Special Issue on Graph Learning.
IEEE Trans. Neural Networks Learn. Syst., September, 2024

Unpacking the exploration-exploitation tradeoff on Snapchat: The relationships between users' exploration-exploitation interests and server log data.
Comput. Hum. Behav., January, 2024

Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank.
CoRR, 2024

Hybrid-DAOs: Enhancing Governance, Scalability, and Compliance in Decentralized Systems.
CoRR, 2024

Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks.
CoRR, 2024

Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems.
CoRR, 2024

Multimodal Graph Benchmark.
CoRR, 2024

How Does Message Passing Improve Collaborative Filtering?
CoRR, 2024

Improving Out-of-Vocabulary Handling in Recommendation Systems.
CoRR, 2024

Node Duplication Improves Cold-start Link Prediction.
CoRR, 2024

Graph Foundation Models.
CoRR, 2024

Neural Scaling Laws on Graphs.
CoRR, 2024

Improving Embedding-Based Retrieval in Friend Recommendation with ANN Query Expansion.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Position: Graph Foundation Models Are Already Here.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

LLaGA: Large Language and Graph Assistant.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Revisiting Link Prediction: a data perspective.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

A Topological Perspective on Demystifying GNN-Based Link Prediction Performance.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning from Graphs Beyond Message Passing Neural Networks.
Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

Explainability and Hate Speech: Structured Explanations Make Social Media Moderators Faster.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, 2024

2023
Graph Data Augmentation for Graph Machine Learning: A Survey.
IEEE Data Eng. Bull., 2023

Graph Transformers for Large Graphs.
CoRR, 2023

Graph Explicit Neural Networks: Explicitly Encoding Graphs for Efficient and Accurate Inference.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

The 3rd International Workshop on Machine Learning on Graphs (MLoG).
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Embedding Based Retrieval in Friend Recommendation.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Large-Scale Graph Neural Networks: The Past and New Frontiers.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

CARL-G: Clustering-Accelerated Representation Learning on Graphs.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

19th International Workshop on Mining and Learning with Graphs (MLG).
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Sketch-Based Anomaly Detection in Streaming Graphs.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Predicting Future Location Categories of Users in a Large Social Platform.
Proceedings of the Seventeenth International AAAI Conference on Web and Social Media, 2023

Linkless Link Prediction via Relational Distillation.
Proceedings of the International Conference on Machine Learning, 2023

Forget Unlearning: Towards True Data-Deletion in Machine Learning.
Proceedings of the International Conference on Machine Learning, 2023

Link Prediction with Non-Contrastive Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Empowering Graph Representation Learning with Test-Time Graph Transformation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion?
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
A Synergistic Approach for Graph Anomaly Detection With Pattern Mining and Feature Learning.
IEEE Trans. Neural Networks Learn. Syst., 2022

Editorial: Computational Behavioral Modeling for Big User Data.
Frontiers Big Data, 2022

A Practical, Progressively-Expressive GNN.
CoRR, 2022

Forget Unlearning: Towards True Data-Deletion in Machine Learning.
CoRR, 2022

Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?
CoRR, 2022

Explaining Graph-level Predictions with Communication Structure-Aware Cooperative Games.
CoRR, 2022

Friend Story Ranking with Edge-Contextual Local Graph Convolutions.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Attributed Graph Modeling with Vertex Replacement Grammars.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

A Practical, Progressively-Expressive GNN.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Flashlight: Scalable Link Prediction With Effective Decoders.
Proceedings of the Learning on Graphs Conference, 2022

17th International Workshop on Mining and Learning with Graphs (MLG).
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Joint International Workshop on Misinformation and Misbehavior Mining on the Web & Making a Credible Web for Tomorrow (MIS2-TrueFact).
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Sunshine with a Chance of Smiles: How Does Weather Impact Sentiment on Social Media?
Proceedings of the Sixteenth International AAAI Conference on Web and Social Media, 2022

From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Graph Condensation for Graph Neural Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Automated Self-Supervised Learning for Graphs.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Is Homophily a Necessity for Graph Neural Networks?
Proceedings of the Tenth International Conference on Learning Representations, 2022

The 1st International Workshop on Federated Learning with Graph Data (FedGraph).
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Imbalanced Graph Classification via Graph-of-Graph Neural Networks.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Extending the Standard REDCap Dictionary Definitions Using REDCap.
Proceedings of the AMIA 2022, 2022

2021
Crime forecasting: a machine learning and computer vision approach to crime prediction and prevention.
Vis. Comput. Ind. Biomed. Art, 2021

KNH: Multi-View Modeling with K-Nearest Hyperplanes Graph for Misinformation Detection.
CoRR, 2021

Graph Neural Networks for Friend Ranking in Large-scale Social Platforms.
Proceedings of the WWW '21: The Web Conference 2021, 2021

The Second International MIS2 Workshop: Misinformation and Misbehavior Mining on the Web.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Online Communication Shifts in the Midst of the Covid-19 Pandemic: A Case Study on Snapchat.
Proceedings of the Fifteenth International AAAI Conference on Web and Social Media, 2021

CEAM: The Effectiveness of Cyclic and Ephemeral Attention Models of User Behavior on Social Platforms.
Proceedings of the Fifteenth International AAAI Conference on Web and Social Media, 2021

Identifying Misinformation from Website Screenshots.
Proceedings of the Fifteenth International AAAI Conference on Web and Social Media, 2021

NED: Niche Detection in User Content Consumption Data.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Action Sequence Augmentation for Early Graph-based Anomaly Detection.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

A Unified View on Graph Neural Networks as Graph Signal Denoising.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social Media.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

FairOD: Fairness-aware Outlier Detection.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Data Augmentation for Graph Neural Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Whole-genome sequencing of patients with rare diseases in a national health system.
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Nat., 2020

A Large-Scale Analysis of Attacker Activity in Compromised Enterprise Accounts.
CoRR, 2020

HiJoD: Semi-Supervised Multi-aspect Detection of Misinformation using Hierarchical Joint Decomposition.
CoRR, 2020

Semi-supervised Multi-aspect Detection of Misinformation Using Hierarchical Joint Decomposition.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020

Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

Social Factors in Closed-Network Content Consumption.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Query-By-Example Spoken Term Detection Using Generative Adversarial Network.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2020

Impact of Minimum Hyperspherical Energy Regularization on Time-Frequency Domain Networks for Singing Voice Separation.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2020

Minority Reports Defense: Defending Against Adversarial Patches.
Proceedings of the Applied Cryptography and Network Security Workshops, 2020

2019
Thrombophilia testing in the inpatient setting: impact of an educational intervention.
BMC Medical Informatics Decis. Mak., 2019

Cybersafety 2019: The 4th Workshop on Computational Methods in Online Misbehavior.
Proceedings of the Companion of The 2019 World Wide Web Conference, 2019

Modeling Dwell Time Engagement on Visual Multimedia.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

FARE: Schema-Agnostic Anomaly Detection in Social Event Logs.
Proceedings of the 2019 IEEE International Conference on Data Science and Advanced Analytics, 2019

SliceNDice: Mining Suspicious Multi-Attribute Entity Groups with Multi-View Graphs.
Proceedings of the 2019 IEEE International Conference on Data Science and Advanced Analytics, 2019

Impact of Contextual Factors on Snapchat Public Sharing.
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

Characterizing and detecting livestreaming chatbots.
Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

2018
Reducing large graphs to small supergraphs: a unified approach.
Soc. Netw. Anal. Min., 2018

False Information on Web and Social Media: A Survey.
CoRR, 2018

Did We Get It Right? Predicting Query Performance in e-Commerce Search.
Proceedings of the SIGIR 2018 Workshop On eCommerce co-located with the 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), 2018

Beyond Outlier Detection: LookOut for Pictorial Explanation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Effectiveness of Generative Adversarial Network for Non-Audible Murmur-to-Whisper Speech Conversion.
Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018

Time-Frequency Masking-Based Speech Enhancement Using Generative Adversarial Network.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Semi-supervised Content-Based Detection of Misinformation via Tensor Embeddings.
Proceedings of the IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, 2018

Novel Spectral Root Cepstral Features for Replay Spoof Detection.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2018

Novel Inter Mixture Weighted GMM Posteriorgram for DNN and GAN-based Voice Conversion.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2018

Time-Frequency Mask-based Speech Enhancement using Convolutional Generative Adversarial Network.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2018

2017
Graph-Based Fraud Detection in the Face of Camouflage.
ACM Trans. Knowl. Discov. Data, 2017

On Summarizing Large-Scale Dynamic Graphs.
IEEE Data Eng. Bull., 2017

LookOut on Time-Evolving Graphs: Succinctly Explaining Anomalies from Any Detector.
CoRR, 2017

OEC: Open-Ended Classification for Future-Proof Link-Fraud Detection.
CoRR, 2017

FLOCK: Combating Astroturfing on Livestreaming Platforms.
Proceedings of the 26th International Conference on World Wide Web, 2017

The Many Faces of Link Fraud.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

M3A: Model, MetaModel and Anomaly Detection for Inter-arrivals of Web Searches and Postings.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

2016
DeltaCon: Principled Massive-Graph Similarity Function with Attribution.
ACM Trans. Knowl. Discov. Data, 2016

M3A: Model, MetaModel, and Anomaly Detection in Web Searches.
CoRR, 2016

BIRDNEST: Bayesian Inference for Ratings-Fraud Detection.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

FRAUDAR: Bounding Graph Fraud in the Face of Camouflage.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

EdgeCentric: Anomaly Detection in Edge-Attributed Networks.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

2015
S-index: Towards Better Metrics for Quantifying Research Impact.
CoRR, 2015

An Empirical Comparison of the Summarization Power of Graph Clustering Methods.
CoRR, 2015

Retweeting Activity on Twitter: Signs of Deception.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

ND-Sync: Detecting Synchronized Fraud Activities.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

TimeCrunch: Interpretable Dynamic Graph Summarization.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014
Spotting Suspicious Link Behavior with fBox: An Adversarial Perspective.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

2013
ALACRITY: Analytics-Driven Lossless Data Compression for Rapid In-Situ Indexing, Storing, and Querying.
Trans. Large Scale Data Knowl. Centered Syst., 2013

ISABELA for effective in situ compression of scientific data.
Concurr. Comput. Pract. Exp., 2013

Challenges in understanding clinical notes: why NLP engines fall short and where background knowledge can help.
Proceedings of the 2013 International Workshop on Data Management & Analytics for Healthcare, 2013

2012
ISOBAR Preconditioner for Effective and High-throughput Lossless Data Compression.
Proceedings of the IEEE 28th International Conference on Data Engineering (ICDE 2012), 2012

Analytics-Driven Lossless Data Compression for Rapid In-situ Indexing, Storing, and Querying.
Proceedings of the Database and Expert Systems Applications, 2012

Improving I/O Throughput with PRIMACY: Preconditioning ID-Mapper for Compressing Incompressibility.
Proceedings of the 2012 IEEE International Conference on Cluster Computing, 2012

2011
S-preconditioner for Multi-fold Data Reduction with Guaranteed User-Controlled Accuracy.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Compressing the Incompressible with ISABELA: In-situ Reduction of Spatio-temporal Data.
Proceedings of the Euro-Par 2011 Parallel Processing - 17th International Conference, 2011

2009
PR: Automatic parallelization of data-parallel statistical computing codes for R in hybrid multi-node and multi-core environments.
Proceedings of the IADIS International Conference Applied Computing 2009, 2009

Heralding New Ringtones of Patient Safety: Blackberry-based Clinical Communication and Telementoring in Laparoscopic Surgery.
Proceedings of the AMIA 2009, 2009


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