Search Results for author: Omkar Bhalerao

Found 3 papers, 3 papers with code

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods

2 code implementations NeurIPS 2021 Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim

Many widely used datasets for graph machine learning tasks have generally been homophilous, where nodes with similar labels connect to each other.

Graph Learning

Edge Proposal Sets for Link Prediction

1 code implementation30 Jun 2021 Abhay Singh, Qian Huang, Sijia Linda Huang, Omkar Bhalerao, Horace He, Ser-Nam Lim, Austin R. Benson

Here, we demonstrate how simply adding a set of edges, which we call a \emph{proposal set}, to the graph as a pre-processing step can improve the performance of several link prediction algorithms.

Experimental Design Link Prediction +1

DEAP Cache: Deep Eviction Admission and Prefetching for Cache

1 code implementation19 Sep 2020 Ayush Mangal, Jitesh Jain, Keerat Kaur Guliani, Omkar Bhalerao

While previous approaches used the past as an indicator of the future, we instead explicitly model the future frequency and recency in a multi-task fashion with prefetching, leveraging the abilities of deep networks to capture futuristic trends and use them for learning eviction and admission.

Density Estimation

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