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Chapter and Conference Paper
Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarks
As social media becomes a hotbed for the spread of misinformation, the crucial task of rumor detection has witnessed promising advances fostered by open-source benchmark datasets. Despite being widely used, we...
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Chapter and Conference Paper
LSCALE: Latent Space Clustering-Based Active Learning for Node Classification
Node classification on graphs is an important task in many practical domains. It usually requires labels for training, which can be difficult or expensive to obtain in practice. Given a budget for labelling, a...
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Chapter and Conference Paper
ARES: Locally Adaptive Reconstruction-Based Anomaly Scoring
How can we detect anomalies: that is, samples that significantly differ from a given set of high-dimensional data, such as images or sensor data? This is a practical problem with numerous applications and is a...
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Article
Autonomous graph mining algorithm search with best performance trade-off
The pervasiveness of graphs today has raised the demand for algorithms to answer various questions: Which products would a user like to purchase given her order list? Which users are buying fake followers? Myr...
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Chapter and Conference Paper
Trust, but Verify: Using Self-supervised Probing to Improve Trustworthiness
Trustworthy machine learning is of primary importance to the practical deployment of deep learning models. While state-of-the-art models achieve astonishingly good performance in terms of accuracy, recent lite...
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Chapter and Conference Paper
Progressive Supervision for Node Classification
Graph Convolution Networks (GCNs) are a powerful approach for the task of node classification, in which GCNs are trained by minimizing the loss over the final-layer predictions. However, a limitation of this t...
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Chapter and Conference Paper
GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs
Finding anomalous snapshots from a graph has garnered huge attention recently. Existing studies address the problem using shallow learning mechanisms such as subspace selection, ego-network, or community analy...
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Chapter and Conference Paper
ONE-M: Modeling the Co-evolution of Opinions and Network Connections
How do opinions of individuals on controversial issues such as marijuana and gay marriage and their underlying social network connections evolve over time? Do people alter their network to have more like-minde...
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Chapter and Conference Paper
Beyond Outliers and on to Micro-clusters: Vision-Guided Anomaly Detection
Given a heatmap for millions of points, what patterns exist in the distributions of point characteristics, and how can we detect them and separate anomalies in a way similar to human vision? In this paper, we ...
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Chapter and Conference Paper
Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions
Given a stream of edge additions and deletions, how can we estimate the count of triangles in it? If we can store only a subset of the edges, how can we obtain unbiased estimates with small variances?
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Chapter and Conference Paper
GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid
Given sensor readings over time from a power grid consisting of nodes (e.g. generators) and edges (e.g. power lines), how can we most accurately detect when an electrical component has failed? More challenging...
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Chapter and Conference Paper
PowerCast: Mining and Forecasting Power Grid Sequences
What will be the power consumption of our institution at 8am for the upcoming days? What will happen to the power consumption of a small factory, if it wants to double (or half) its production? Technologies as...
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Chapter and Conference Paper
zooRank: Ranking Suspicious Entities in Time-Evolving Tensors
Most user-based websites such as social networks (Twitter, Facebook) and e-commerce websites (Amazon) have been targets of group fraud (multiple users working together for malicious purposes). How can we bette...
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Chapter and Conference Paper
The Message or the Messenger? Inferring Virality and Diffusion Structure from Online Petition Signature Data
Goel et al. [14] examined diffusion data from Twitter to conclude that online petitions are shared more virally than other types of content. Their definition of structural virality, which measures the extent to w...
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Chapter and Conference Paper
BeatLex: Summarizing and Forecasting Time Series with Patterns
Given time-series data such as electrocardiogram (ECG) readings, or motion capture data, how can we succintly summarize the data in a way that robustly identifies patterns that appear repeatedly? How can we th...
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Chapter and Conference Paper
Matrices, Compression, Learning Curves: Formulation, and the GroupNteach Algorithms
Suppose you are a teacher, and have to convey a set of object-property pairs (‘lions eat meat’). A good teacher will convey a lot of information, with little effort on the student side. What is the best and mo...
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Chapter and Conference Paper
M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees
Given a large-scale and high-order tensor, how can we find dense blocks in it? Can we find them in near-linear time but with a quality guarantee? Extensive previous work has shown that dense blocks in tensors ...
