Nikhil Rao

Orcid: 0000-0003-0281-932X

Affiliations:
  • Amazon, Palo Alto, CA, USA
  • Technicolor Research and Innovation, Los Altos, CA, USA
  • University of Texas at Austin, Department of Computer Science, TX, USA
  • University of Wisconsin - Madison, Department of Electrical and Computer Engineering, WI, USA


According to our database1, Nikhil Rao authored at least 58 papers between 2011 and 2023.

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Bibliography

2023
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation.
CoRR, 2023

You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction.
CoRR, 2023

Search Behavior Prediction: A Hypergraph Perspective.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Text Enriched Sparse Hyperbolic Graph Convolutional Networks.
CoRR, 2022

Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search.
CoRR, 2022

ALLIE: Active Learning on Large-scale Imbalanced Graphs.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022


ANTHEM: Attentive Hyperbolic Entity Model for Product Search.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Task-Agnostic Graph Explanations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Maximizing and Satisficing in Multi-armed Bandits with Graph Information.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

AutoGDA: Automated Graph Data Augmentation for Node Classification.
Proceedings of the Learning on Graphs Conference, 2022

Learning Backward Compatible Embeddings.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Hyperbolic Neural Networks: Theory, Architectures and Applications.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Graph-based Multilingual Language Model: Leveraging Product Relations for Search Relevance.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Cluster-and-Conquer: A Framework For Time-Series Forecasting.
CoRR, 2021

Pure Exploration in Multi-armed Bandits with Graph Side Information.
CoRR, 2021

Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Learning with Little Data: Industry Challenges and Innovations.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bipartite Dynamic Representations for Abuse Detection.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Workshop on Data-Efficient Machine Learning (DeMaL).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Finding Needles in Heterogeneous Haystacks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Learning Robust Models for e-Commerce Product Search.
CoRR, 2020

Language-Agnostic Representation Learning for Product Search on E-Commerce Platforms.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Regularized Graph Convolutional Networks for Short Text Classification.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Scalable Feature Selection for (Multitask) Gradient Boosted Trees.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Learning Robust Models for e-Commerce Product Search.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Identifying Facet Mismatches In Search Via Micrographs.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018
A Sparse Topic Model for Extracting Aspect-Specific Summaries from Online Reviews.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Dynamic Word Embeddings for Evolving Semantic Discovery.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

2017
Discovery of Evolving Semantics through Dynamic Word Embedding Learning.
CoRR, 2017

A Simple Approach to Learn Polysemous Word Embeddings.
CoRR, 2017

Matrix Factorization with Side and Higher Order Information.
CoRR, 2017

The group k-support norm for learning with structured sparsity.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

On Learning High Dimensional Structured Single Index Models.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Classification With the Sparse Group Lasso.
IEEE Trans. Signal Process., 2016

Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Structured Sparse Regression via Greedy Hard Thresholding.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Goal-Directed Inductive Matrix Completion.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015
Forward-Backward Greedy Algorithms for Atomic Norm Regularization.
IEEE Trans. Signal Process., 2015

Temporal Regularized Matrix Factorization.
CoRR, 2015

Optimal Low-Rank Tensor Recovery from Separable Measurements: Four Contractions Suffice.
CoRR, 2015

Learning Single Index Models in High Dimensions.
CoRR, 2015

Sparse and Low-Rank Tensor Decomposition.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Collaborative Filtering with Graph Information: Consistency and Scalable Methods.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

PU matrix completion with graph information.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

2014
Logistic Regression with Structured Sparsity.
CoRR, 2014

Forward - Backward greedy algorithms for signal demixing.
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2013
Sparse Overlapping Sets Lasso for Multitask Learning and its Application to fMRI Analysis.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

A greedy forward-backward algorithm for atomic norm constrained minimization.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Universal Measurement Bounds for Structured Sparse Signal Recovery.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Correlated gaussian designs for compressive imaging.
Proceedings of the 19th IEEE International Conference on Image Processing, 2012

A clustering approach to optimize online dictionary learning.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011
Tight Measurement Bounds for Exact Recovery of Structured Sparse Signals.
CoRR, 2011

Convex approaches to model wavelet sparsity patterns.
Proceedings of the 18th IEEE International Conference on Image Processing, 2011


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