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ORCIDNikhil Rao 0001
Nikhil S. Rao
Person information
- affiliation: Amazon, Palo Alto, CA, USA
- affiliation: Technicolor Research and Innovation, Los Altos, CA, USA
- affiliation: University of Texas at Austin, Department of Computer Science, TX, USA
- affiliation: University of Wisconsin - Madison, Department of Electrical and Computer Engineering, WI, USA
Other persons with the same name
- Nikhil Rao — disambiguation page
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Journal Articles
- 2023
[j3]Wenqing Zheng, Edward W. Huang, Nikhil Rao, Zhangyang Wang, Karthik Subbian:
You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction. Trans. Mach. Learn. Res. 2023 (2023)- 2016
- [j2]Nikhil Rao, Robert D. Nowak, Christopher R. Cox, Timothy T. Rogers:
Classification With the Sparse Group Lasso. IEEE Trans. Signal Process. 64(2): 448-463 (2016) - 2015
- [j1]Nikhil Rao, Parikshit Shah, Stephen J. Wright:
Forward-Backward Greedy Algorithms for Atomic Norm Regularization. IEEE Trans. Signal Process. 63(21): 5798-5811 (2015)
Conference and Workshop Papers
- 2024
- [c43]Canwen Xu, Corby Rosset, Ethan C. Chau, Luciano Del Corro, Shweti Mahajan, Julian J. McAuley, Jennifer Neville, Ahmed Awadallah, Nikhil Rao:
Automatic Pair Construction for Contrastive Post-training. NAACL-HLT (Findings) 2024: 149-162 - [c42]Qi Chen
, Xiubo Geng, Corby Rosset, Carolyn Buractaon, Jingwen Lu, Tao Shen, Kun Zhou, Chenyan Xiong, Yeyun Gong, Paul N. Bennett, Nick Craswell, Xing Xie, Fan Yang, Bryan Tower, Nikhil Rao, Anlei Dong, Wenqi Jiang, Zheng Liu, Mingqin Li, Chuanjie Liu, Zengzhong Li, Rangan Majumder, Jennifer Neville, Andy Oakley, Knut Magne Risvik, Harsha Vardhan Simhadri, Manik Varma, Yujing Wang, Linjun Yang, Mao Yang, Ce Zhang:
MS MARCO Web Search: A Large-scale Information-rich Web Dataset with Millions of Real Click Labels. WWW (Companion Volume) 2024: 292-301 - 2023
- [c41]Nurendra Choudhary, Nikhil Rao, Chandan K. Reddy:
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach. NeurIPS 2023 - [c40]Yan Han, Edward W. Huang, Wenqing Zheng, Nikhil Rao, Zhangyang Wang, Karthik Subbian:
Search Behavior Prediction: A Hypergraph Perspective. WSDM 2023: 697-705 - 2022
- [c39]Wenqing Zheng, Edward W. Huang, Nikhil Rao, Sumeet Katariya, Zhangyang Wang, Karthik Subbian:
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods. ICLR 2022 - [c38]Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Chandan K. Reddy:
Graph-based Multilingual Language Model: Leveraging Product Relations for Search Relevance. KDD 2022: 2789-2799 - [c37]Weihua Hu, Rajas Bansal, Kaidi Cao, Nikhil Rao, Karthik Subbian, Jure Leskovec:
Learning Backward Compatible Embeddings. KDD 2022: 3018-3028 - [c36]Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy:
Hyperbolic Neural Networks: Theory, Architectures and Applications. KDD 2022: 4778-4779 - [c35]Tong Zhao, Xianfeng Tang, Danqing Zhang, Haoming Jiang, Nikhil Rao, Yiwei Song, Pallav Agrawal, Karthik Subbian, Bing Yin, Meng Jiang:
AutoGDA: Automated Graph Data Augmentation for Node Classification. LoG 2022: 32 - [c34]Parth Thaker, Mohit Malu, Nikhil Rao, Gautam Dasarathy:
Maximizing and Satisficing in Multi-armed Bandits with Graph Information. NeurIPS 2022 - [c33]Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward W. Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji:
Task-Agnostic Graph Explanations. NeurIPS 2022 - [c32]Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
ANTHEM: Attentive Hyperbolic Entity Model for Product Search. WSDM 2022: 161-171 - [c31]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [c30]Limeng Cui, Xianfeng Tang, Sumeet Katariya, Nikhil Rao, Pallav Agrawal, Karthik Subbian, Dongwon Lee:
ALLIE: Active Learning on Large-scale Imbalanced Graphs. WWW 2022: 690-698 - 2021
- [c29]Bijaya Adhikari, Liangyue Li, Nikhil Rao, Karthik Subbian:
Finding Needles in Heterogeneous Haystacks. AAAI 2021: 15232-15239 - [c28]Andrew Z. Wang, Rex Ying, Pan Li, Nikhil Rao, Karthik Subbian, Jure Leskovec:
Bipartite Dynamic Representations for Abuse Detection. KDD 2021: 3638-3648 - [c27]Sumeet Katariya, Nikhil Rao, Chandan K. Reddy:
Workshop on Data-Efficient Machine Learning (DeMaL). KDD 2021: 4135-4136 - [c26]Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs. NeurIPS 2021: 23440-23451 - [c25]Nikhil Rao:
Learning with Little Data: Industry Challenges and Innovations. SIGIR 2021: 2625-2626 - [c24]Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs. WWW 2021: 1373-1384 - 2020
- [c23]Thanh V. Nguyen, Nikhil Rao, Karthik Subbian:
Learning Robust Models for e-Commerce Product Search. ACL 2020: 6861-6869 - [c22]Liwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh:
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering. AISTATS 2020: 776-787 - [c21]Cuize Han, Nikhil Rao, Daria Sorokina, Karthik Subbian:
Scalable Feature Selection for (Multitask) Gradient Boosted Trees. AISTATS 2020: 885-894 - [c20]Kshitij Tayal, Nikhil Rao, Saurabh Agarwal, Xiaowei Jia, Karthik Subbian, Vipin Kumar:
Regularized Graph Convolutional Networks for Short Text Classification. COLING (Industry) 2020: 236-242 - [c19]Aman Ahuja, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Language-Agnostic Representation Learning for Product Search on E-Commerce Platforms. WSDM 2020: 7-15 - 2019
- [c18]Sriram Srinivasan, Nikhil S. Rao, Karthik Subbian, Lise Getoor:
Identifying Facet Mismatches In Search Via Micrographs. CIKM 2019: 1663-1672 - 2018
- [c17]Zijun Yao, Yifan Sun, Weicong Ding, Nikhil Rao, Hui Xiong:
Dynamic Word Embeddings for Evolving Semantic Discovery. WSDM 2018: 673-681 - [c16]Vineeth Rakesh, Weicong Ding, Aman Ahuja, Nikhil Rao, Yifan Sun, Chandan K. Reddy:
A Sparse Topic Model for Extracting Aspect-Specific Summaries from Online Reviews. WWW 2018: 1573-1582 - 2017
- [c15]Ravi Ganti, Nikhil Rao, Laura Balzano, Rebecca Willett, Robert D. Nowak:
On Learning High Dimensional Structured Single Index Models. AAAI 2017: 1898-1904 - [c14]Nikhil Rao, Miroslav Dudík, Zaïd Harchaoui:
The group k-support norm for learning with structured sparsity. ICASSP 2017: 2402-2406 - 2016
- [c13]Si Si, Kai-Yang Chiang, Cho-Jui Hsieh, Nikhil Rao, Inderjit S. Dhillon:
Goal-Directed Inductive Matrix Completion. KDD 2016: 1165-1174 - [c12]Hsiang-Fu Yu, Nikhil Rao, Inderjit S. Dhillon:
Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction. NIPS 2016: 847-855 - [c11]Prateek Jain, Nikhil Rao, Inderjit S. Dhillon:
Structured Sparse Regression via Greedy Hard Thresholding. NIPS 2016: 1516-1524 - 2015
- [c10]Nagarajan Natarajan, Nikhil Rao, Inderjit S. Dhillon:
PU matrix completion with graph information. CAMSAP 2015: 37-40 - [c9]Nikhil Rao, Hsiang-Fu Yu, Pradeep Ravikumar, Inderjit S. Dhillon:
Collaborative Filtering with Graph Information: Consistency and Scalable Methods. NIPS 2015: 2107-2115 - [c8]Parikshit Shah, Nikhil Rao, Gongguo Tang:
Sparse and Low-Rank Tensor Decomposition. NIPS 2015: 2548-2556 - 2014
- [c7]Nikhil Rao, Parikshit Shah, Stephen J. Wright:
Forward - Backward greedy algorithms for signal demixing. ACSSC 2014: 437-441 - 2013
- [c6]Nikhil Rao, Parikshit Shah, Stephen J. Wright, Robert D. Nowak:
A greedy forward-backward algorithm for atomic norm constrained minimization. ICASSP 2013: 5885-5889 - [c5]Nikhil S. Rao, Christopher R. Cox, Robert D. Nowak, Timothy T. Rogers:
Sparse Overlapping Sets Lasso for Multitask Learning and its Application to fMRI Analysis. NIPS 2013: 2202-2210 - 2012
- [c4]Nikhil Rao, Fatih Porikli:
A clustering approach to optimize online dictionary learning. ICASSP 2012: 1293-1296 - [c3]Nikhil S. Rao, Robert D. Nowak:
Correlated gaussian designs for compressive imaging. ICIP 2012: 921-924 - [c2]Nikhil Rao, Ben Recht, Robert D. Nowak:
Universal Measurement Bounds for Structured Sparse Signal Recovery. AISTATS 2012: 942-950 - 2011
- [c1]Nikhil S. Rao, Robert D. Nowak, Stephen J. Wright, Nick G. Kingsbury:
Convex approaches to model wavelet sparsity patterns. ICIP 2011: 1917-1920
Informal and Other Publications
- 2024
- [i32]Corby Rosset, Ho-Lam Chung, Guanghui Qin, Ethan C. Chau, Zhuo Feng, Ahmed Awadallah, Jennifer Neville, Nikhil Rao:
Researchy Questions: A Dataset of Multi-Perspective, Decompositional Questions for LLM Web Agents. CoRR abs/2402.17896 (2024) - [i31]Qi Chen, Xiubo Geng, Corby Rosset, Carolyn Buractaon, Jingwen Lu, Tao Shen, Kun Zhou, Chenyan Xiong, Yeyun Gong, Paul N. Bennett, Nick Craswell, Xing Xie, Fan Yang, Bryan Tower, Nikhil Rao, Anlei Dong, Wenqi Jiang, Zheng Liu, Mingqin Li, Chuanjie Liu, Zengzhong Li, Rangan Majumder, Jennifer Neville, Andy Oakley, Knut Magne Risvik, Harsha Vardhan Simhadri, Manik Varma, Yujing Wang, Linjun Yang, Mao Yang, Ce Zhang:
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels. CoRR abs/2405.07526 (2024) - 2023
- [i30]Wenqing Zheng, Edward W. Huang, Nikhil Rao, Zhangyang Wang, Karthik Subbian:
You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction. CoRR abs/2302.14189 (2023) - [i29]Jiong Zhu, Aishwarya Reganti, Edward W. Huang, Charles Dickens, Nikhil Rao, Karthik Subbian, Danai Koutra:
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation. CoRR abs/2305.09887 (2023) - [i28]Canwen Xu, Corby Rosset, Luciano Del Corro, Shweti Mahajan, Julian J. McAuley, Jennifer Neville, Ahmed Hassan Awadallah, Nikhil Rao:
Contrastive Post-training Large Language Models on Data Curriculum. CoRR abs/2310.02263 (2023) - [i27]Nurendra Choudhary, Nikhil Rao, Chandan K. Reddy:
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach. CoRR abs/2310.18918 (2023) - 2022
- [i26]Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward W. Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji:
Task-Agnostic Graph Explanations. CoRR abs/2202.08335 (2022) - [i25]Weihua Hu, Rajas Bansal, Kaidi Cao, Nikhil Rao, Karthik Subbian, Jure Leskovec:
Learning Backward Compatible Embeddings. CoRR abs/2206.03040 (2022) - [i24]Chandan K. Reddy, Lluís Màrquez, Fran Valero, Nikhil Rao, Hugo Zaragoza, Sambaran Bandyopadhyay, Arnab Biswas, Anlu Xing, Karthik Subbian:
Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search. CoRR abs/2206.06588 (2022) - [i23]Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Chandan K. Reddy:
Text Enriched Sparse Hyperbolic Graph Convolutional Networks. CoRR abs/2207.02368 (2022) - [i22]Yan Han, Edward W. Huang, Wenqing Zheng, Nikhil Rao, Zhangyang Wang, Karthik Subbian:
Search Behavior Prediction: A Hypergraph Perspective. CoRR abs/2211.13328 (2022) - 2021
- [i21]Parth K. Thaker, Nikhil Rao, Mohit Malu, Gautam Dasarathy:
Pure Exploration in Multi-armed Bandits with Graph Side Information. CoRR abs/2108.01152 (2021) - [i20]Cuize Han, Nikhil Rao, Daria Sorokina, Karthik Subbian:
Scalable Feature Selection for (Multitask) Gradient Boosted Trees. CoRR abs/2109.01965 (2021) - [i19]Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs. CoRR abs/2110.13522 (2021) - [i18]Reese Pathak, Rajat Sen, Nikhil Rao, N. Benjamin Erichson, Michael I. Jordan, Inderjit S. Dhillon:
Cluster-and-Conquer: A Framework For Time-Series Forecasting. CoRR abs/2110.14011 (2021) - [i17]Wenqing Zheng, Edward W. Huang, Nikhil Rao, Sumeet Katariya, Zhangyang Wang, Karthik Subbian:
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods. CoRR abs/2111.04840 (2021) - 2020
- [i16]Thanh Van Nguyen, Nikhil Rao, Karthik Subbian:
Learning Robust Models for e-Commerce Product Search. CoRR abs/2005.03624 (2020) - [i15]Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs. CoRR abs/2012.13023 (2020) - 2019
- [i14]Liwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh:
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering. CoRR abs/1905.12217 (2019) - 2017
- [i13]Zijun Yao, Yifan Sun, Weicong Ding, Nikhil Rao, Hui Xiong:
Discovery of Evolving Semantics through Dynamic Word Embedding Learning. CoRR abs/1703.00607 (2017) - [i12]Vatsal Shah, Nikhil Rao, Weicong Ding:
Matrix Factorization with Side and Higher Order Information. CoRR abs/1705.02047 (2017) - [i11]Yifan Sun, Nikhil Rao, Weicong Ding:
A Simple Approach to Learn Polysemous Word Embeddings. CoRR abs/1707.01793 (2017) - 2016
- [i10]Prateek Jain, Nikhil Rao, Inderjit S. Dhillon:
Structured Sparse Regression via Greedy Hard-Thresholding. CoRR abs/1602.06042 (2016) - [i9]Nikhil Rao, Ravi Ganti, Laura Balzano, Rebecca Willett, Robert D. Nowak:
On Learning High Dimensional Structured Single Index Models. CoRR abs/1603.03980 (2016) - 2015
- [i8]Parikshit Shah, Nikhil Rao, Gongguo Tang:
Optimal Low-Rank Tensor Recovery from Separable Measurements: Four Contractions Suffice. CoRR abs/1505.04085 (2015) - [i7]Ravi Ganti, Nikhil Rao, Rebecca M. Willett, Robert D. Nowak:
Learning Single Index Models in High Dimensions. CoRR abs/1506.08910 (2015) - [i6]Hsiang-Fu Yu, Nikhil Rao, Inderjit S. Dhillon:
Temporal Regularized Matrix Factorization. CoRR abs/1509.08333 (2015) - 2014
- [i5]Nikhil S. Rao, Robert D. Nowak, Christopher R. Cox, Timothy T. Rogers:
Logistic Regression with Structured Sparsity. CoRR abs/1402.4512 (2014) - [i4]Nikhil Rao, Parikshit Shah, Stephen J. Wright:
Forward - Backward Greedy Algorithms for Atomic Norm Regularization. CoRR abs/1404.5692 (2014) - 2013
- [i3]Nikhil S. Rao, Christopher R. Cox, Robert D. Nowak, Timothy T. Rogers:
Sparse Overlapping Sets Lasso for Multitask Learning and its Application to fMRI Analysis. CoRR abs/1311.5422 (2013) - 2011
- [i2]Nikhil S. Rao, Robert D. Nowak, Stephen J. Wright, Nick G. Kingsbury:
Convex Approaches to Model Wavelet Sparsity Patterns. CoRR abs/1104.4385 (2011) - [i1]Nikhil Rao, Benjamin Recht, Robert D. Nowak:
Tight Measurement Bounds for Exact Recovery of Structured Sparse Signals. CoRR abs/1106.4355 (2011)
Coauthor Index
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