9 citations · 23 across the 9 of their papers we have counts for
9 papers
Federated Classification in Hyperbolic Spaces via Secure Aggregation of Convex Hulls
Saurav Prakash, Jin Sima, Chao Pan +2
Hierarchical and tree-like data sets arise in many applications, including language processing, graph data mining, phylogeny and genomics. It is known that tree-like data cannot be…
Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection
Eli Chien, Wei-Ning Chen, Chao Pan +3
GNNs can inadvertently expose sensitive user information and interactions through their model predictions. To address these privacy concerns, Differential Privacy (DP) protocols ar…
Unlearning Graph Classifiers with Limited Data Resources
Chao Pan, Eli Chien, Olgica Milenkovic
As the demand for user privacy grows, controlled data removal (machine unlearning) is becoming an important feature of machine learning models for data-sensitive Web applications s…
On the Study of Sample Complexity for Polynomial Neural Networks
Chao Pan, Chuanyi Zhang
As a general type of machine learning approach, artificial neural networks have established state-of-art benchmarks in many pattern recognition and data analysis tasks. Among vario…
Certified Graph Unlearning
Eli Chien, Chao Pan, Olgica Milenkovic
Graph-structured data is ubiquitous in practice and often processed using graph neural networks (GNNs). With the adoption of recent laws ensuring the ``right to be forgotten'', the…
Provably Accurate and Scalable Linear Classifiers in Hyperbolic Spaces
Chao Pan, Eli Chien, Puoya Tabaghi +2
Many high-dimensional practical data sets have hierarchical structures induced by graphs or time series. Such data sets are hard to process in Euclidean spaces and one often seeks…
Highly Scalable and Provably Accurate Classification in Poincare Balls
Eli Chien, Chao Pan, Puoya Tabaghi +1
Many high-dimensional and large-volume data sets of practical relevance have hierarchical structures induced by trees, graphs or time series. Such data sets are hard to process in…
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks
Eli Chien, Chao Pan, Jianhao Peng +1
Hypergraphs are used to model higher-order interactions amongst agents and there exist many practically relevant instances of hypergraph datasets. To enable efficient processing of…
Linear Classifiers in Product Space Forms
Puoya Tabaghi, Chao Pan, Eli Chien +2
Embedding methods for product spaces are powerful techniques for low-distortion and low-dimensional representation of complex data structures. Here, we address the new problem of l…