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05/17/2023
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation
Distributed training of GNNs enables learning on massive graphs (e.g., s...
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02/27/2023
You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction
Link prediction is central to many real-world applications, but its perf...
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11/23/2022
Search Behavior Prediction: A Hypergraph Perspective
Although the bipartite shopping graphs are straightforward to model sear...
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08/28/2022
ECP SOLLVE: Validation and Verification Testsuite Status Update and Compiler Insight for OpenMP
The OpenMP language continues to evolve with every new specification rel...
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07/06/2022
Text Enriched Sparse Hyperbolic Graph Convolutional Networks
Heterogeneous networks, which connect informative nodes containing text ...
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06/14/2022
Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search
Improving the quality of search results can significantly enhance users ...
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06/07/2022
Learning Backward Compatible Embeddings
Embeddings, low-dimensional vector representation of objects, are fundam...
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02/16/2022
Task-Agnostic Graph Explanations
Graph Neural Networks (GNNs) have emerged as powerful tools to encode gr...
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11/08/2021
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
Graph Neural Networks (GNNs) have achieved state of the art performance ...
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10/26/2021
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs
Logical reasoning over Knowledge Graphs (KGs) is a fundamental technique...
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09/05/2021
Scalable Feature Selection for (Multitask) Gradient Boosted Trees
Gradient Boosted Decision Trees (GBDTs) are widely used for building ran...
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08/02/2021
Pure Exploration in Multi-armed Bandits with Graph Side Information
We study pure exploration in multi-armed bandits with graph side-informa...
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12/23/2020
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs
Knowledge Graphs (KGs) are ubiquitous structures for information storage...
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05/07/2020
Learning Robust Models for e-Commerce Product Search
Showing items that do not match search query intent degrades customer ex...
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05/29/2019
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering
In this paper, we consider recommender systems with side information in ...
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07/06/2017
A Simple Approach to Learn Polysemous Word Embeddings
Many NLP applications require disambiguating polysemous words. Existing ...
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05/04/2017
Matrix Factorization with Side and Higher Order Information
The problem of predicting unobserved entries of a partially observed mat...
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03/02/2017
Discovery of Evolving Semantics through Dynamic Word Embedding Learning
During the course of human language evolution, the semantic meanings of ...
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03/13/2016
On Learning High Dimensional Structured Single Index Models
Single Index Models (SIMs) are simple yet flexible semi-parametric model...
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02/19/2016
Structured Sparse Regression via Greedy Hard-Thresholding
Several learning applications require solving high-dimensional regressio...
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09/28/2015
High-dimensional Time Series Prediction with Missing Values
High-dimensional time series prediction is needed in applications as div...
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06/30/2015
Learning Single Index Models in High Dimensions
Single Index Models (SIMs) are simple yet flexible semi-parametric model...
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05/15/2015
Optimal Low-Rank Tensor Recovery from Separable Measurements: Four Contractions Suffice
Tensors play a central role in many modern machine learning and signal p...
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04/23/2014
Forward - Backward Greedy Algorithms for Atomic Norm Regularization
In many signal processing applications, the aim is to reconstruct a sign...
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02/18/2014
Classification with Sparse Overlapping Groups
Classification with a sparsity constraint on the solution plays a centra...
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11/20/2013
Sparse Overlapping Sets Lasso for Multitask Learning and its Application to fMRI Analysis
Multitask learning can be effective when features useful in one task are...
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09/14/2012
Signal Recovery in Unions of Subspaces with Applications to Compressive Imaging
In applications ranging from communications to genetics, signals can be ...
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06/22/2011
