26 citations · 65 across the 9 of their papers we have counts for
11 papers
Long-VMNet: Accelerating Long-Form Video Understanding via Fixed Memory
Saket Gurukar, Asim Kadav
Long-form video understanding is essential for various applications such as video retrieval, summarizing, and question answering. Yet, traditional approaches demand substantial com…
HeteroMILE: a Multi-Level Graph Representation Learning Framework for Heterogeneous Graphs
Yue Zhang, Yuntian He, Saket Gurukar +1
Heterogeneous graphs are ubiquitous in real-world applications because they can represent various relationships between different types of entities. Therefore, learning embeddings…
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks
Saket Gurukar, Shaileshh Bojja Venkatakrishnan, Balaraman Ravindran +1
Graph convolutional networks (GCNs) have achieved huge success in several machine learning (ML) tasks on graph-structured data. Recently, several sampling techniques have been prop…
FairMILE: Towards an Efficient Framework for Fair Graph Representation Learning
Yuntian He, Saket Gurukar, Srinivasan Parthasarathy
Graph representation learning models have demonstrated great capability in many real-world applications. Nevertheless, prior research indicates that these models can learn biased r…
MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest
Saket Gurukar, Nikil Pancha, Andrew Zhai +5
Graph Convolutional Networks (GCN) can efficiently integrate graph structure and node features to learn high-quality node embeddings. These embeddings can then be used for several…
FairEGM: Fair Link Prediction and Recommendation via Emulated Graph Modification
Sean Current, Yuntian He, Saket Gurukar +1
As machine learning becomes more widely adopted across domains, it is critical that researchers and ML engineers think about the inherent biases in the data that may be perpetuated…
A Machine Learning Model for Nowcasting Epidemic Incidence
Saumya Yashmohini Sahai, Saket Gurukar, Wasiur R. KhudaBukhsh +2
Due to delay in reporting, the daily national and statewide COVID-19 incidence counts are often unreliable and need to be estimated from recent data. This process is known in econo…
Towards Quantifying the Distance between Opinions
Saket Gurukar, Deepak Ajwani, Sourav Dutta +3
Increasingly, critical decisions in public policy, governance, and business strategy rely on a deeper understanding of the needs and opinions of constituent members (e.g. citizens,…
Twitter Watch: Leveraging Social Media to Monitor and Predict Collective-Efficacy of Neighborhoods
Moniba Keymanesh, Saket Gurukar, Bethany Boettner +3
Sociologists associate the spatial variation of crime within an urban setting, with the concept of collective efficacy. The collective efficacy of a neighborhood is defined as soci…
Network Representation Learning: Consolidation and Renewed Bearing
Saket Gurukar, Priyesh Vijayan, Aakash Srinivasan +9
Graphs are a natural abstraction for many problems where nodes represent entities and edges represent a relationship across entities. An important area of research that has emerged…
MILE: A Multi-Level Framework for Scalable Graph Embedding
Jiongqian Liang, Saket Gurukar, Srinivasan Parthasarathy
Recently there has been a surge of interest in designing graph embedding methods. Few, if any, can scale to a large-sized graph with millions of nodes due to both computational com…