Solving SDD linear systems in nearly mlog1/2n time. - Michael B. Cohen; Rasmus Kyng; Gary L. Miller; Jakub W. Pachocki; Richard Peng; Anup B. Rao; Shen Chen Xu (STOC, 2014)

Preconditioning in Expectation. - Michael B. Cohen; Rasmus Kyng; Jakub W. Pachocki; Richard Peng; Anup B. Rao (CoRR, 2014)

Stochastic Block Model and Community Detection in Sparse Graphs: A spectral algorithm with optimal rate of recovery. - Peter Chin 001; Anup Rao 002; Van Vu (COLT, 2015)

Algorithms for Lipschitz Learning on Graphs. - Rasmus Kyng; Anup Rao 002; Sushant Sachdeva; Daniel A. Spielman (COLT, 2015)

Fast, Provable Algorithms for Isotonic Regression in all L_p-norms. - Rasmus Kyng; Anup Rao 002; Sushant Sachdeva (NIPS, 2015)

Fast, Provable Algorithms for Isotonic Regression in all ℓp-norms. - Rasmus Kyng; Anup Rao 002; Sushant Sachdeva (CoRR, 2015)

Agnostic Estimation of Mean and Covariance. - Kevin A. Lai; Anup B. Rao; Santosh S. Vempala (FOCS, 2016)

Determinant-Preserving Sparsification of SDDM Matrices with Applications to Counting and Sampling Spanning Trees. - David Durfee; John Peebles; Richard Peng; Anup B. Rao (FOCS, 2017)

Almost-linear-time algorithms for Markov chains and new spectral primitives for directed graphs. - Michael B. Cohen; Jonathan A. Kelner; John Peebles; Richard Peng; Anup B. Rao; Aaron Sidford; Adrian Vladu (STOC, 2017)

Sampling random spanning trees faster than matrix multiplication. - David Durfee; Rasmus Kyng; John Peebles; Anup B. Rao; Sushant Sachdeva (STOC, 2017)

Concave Flow on Small Depth Directed Networks. - Tung Mai; Richard Peng; Anup B. Rao; Vijay V. Vazirani (CoRR, 2017)

Stochastic Low-Rank Bandits. - Branislav Kveton; Csaba Szepesvári; Anup Rao 002; Zheng Wen 002; Yasin Abbasi-Yadkori; S. Muthukrishnan 001 (CoRR, 2017)

Solving Directed Laplacian Systems in Nearly-Linear Time through Sparse LU Factorizations. - Michael B. Cohen; Jonathan A. Kelner; Rasmus Kyng; John Peebles; Richard Peng; Anup B. Rao; Aaron Sidford (FOCS, 2018)

New Insights into Bootstrapping for Bandits. - Sharan Vaswani; Branislav Kveton; Zheng Wen 002; Anup Rao 002; Mark Schmidt 001; Yasin Abbasi-Yadkori (CoRR, 2018)

Higher-order Graph Convolutional Networks. - John Boaz Lee; Ryan A. Rossi; Xiangnan Kong; Sungchul Kim; Eunyee Koh; Anup Rao 002 (CoRR, 2018)

Higher-order Spectral Clustering for Heterogeneous Graphs. - Aldo G. Carranza; Ryan A. Rossi; Anup Rao 002; Eunyee Koh (CoRR, 2018)

Bridging Network Embedding and Graph Summarization. - Di Jin 003; Ryan A. Rossi; Danai Koutra; Eunyee Koh; Sungchul Kim; Anup Rao 002 (CoRR, 2018)

Sample Efficient Graph-Based Optimization with Noisy Observations. - Thanh Tan Nguyen; Ali Shameli; Yasin Abbasi-Yadkori; Anup Rao 002; Branislav Kveton (AISTATS, 2019)

Graph Convolutional Networks with Motif-based Attention. - John Boaz Lee; Ryan A. Rossi; Xiangnan Kong; Sungchul Kim; Eunyee Koh; Anup Rao 002 (CIKM, 2019)

Latent Network Summarization: Bridging Network Embedding and Summarization. - Di Jin 003; Ryan A. Rossi; Eunyee Koh; Sungchul Kim; Anup Rao 002; Danai Koutra (KDD, 2019)

Hacd: Hierarchical Agglomerative Community Detection In Social Networks. - Ekta Gujral; Evangelos E. Papalexakis; Georgios Theocharous; Anup B. Rao (MLSP, 2019)

On Densification for Minwise Hashing. - Tung Mai; Anup Rao 002; Matt Kapilevich; Ryan A. Rossi; Yasin Abbasi-Yadkori; Ritwik Sinha (UAI, 2019)

Efficient Second-Order Shape-Constrained Function Fitting. - David Durfee; Yu Gao 001; Anup B. Rao; Sebastian Wild (WADS, 2019)

Heterogeneous Network Motifs. - Ryan A. Rossi; Nesreen K. Ahmed; Aldo G. Carranza; David Arbour; Anup Rao 002; Sungchul Kim; Eunyee Koh (CoRR, 2019)

Higher-Order Ranking and Link Prediction: From Closing Triangles to Closing Higher-Order Motifs. - Ryan A. Rossi; Anup Rao 002; Sungchul Kim; Eunyee Koh; Nesreen K. Ahmed; Gang Wu 013 (CoRR, 2019)

Higher-order Clustering in Complex Heterogeneous Networks. - Aldo G. Carranza; Ryan A. Rossi; Anup Rao 002; Eunyee Koh (KDD, 2020)

Model Selection in Contextual Stochastic Bandit Problems. - Aldo Pacchiano; My Phan; Yasin Abbasi-Yadkori; Anup Rao 002; Julian Zimmert; Tor Lattimore; Csaba Szepesvári (NeurIPS, 2020)

Dynamic Clustering with Discrete Time Event Prediction. - Karan Aggarwal; Georgios Theocharous; Anup B. Rao (SIGIR, 2020)

Approximate Maximum Matching in Random Streams. - Alireza Farhadi 001; Mohammad Taghi Hajiaghayi; Tung Mai; Anup Rao 002; Ryan A. Rossi (SODA, 2020)

A Structural Graph Representation Learning Framework. - Ryan A. Rossi; Nesreen K. Ahmed; Eunyee Koh; Sungchul Kim; Anup Rao 002; Yasin Abbasi-Yadkori (WSDM, 2020)

Real-Time Clustering for Large Sparse Online Visitor Data. - Gromit Yeuk-Yin Chan; Fan Du; Ryan A. Rossi; Anup B. Rao; Eunyee Koh; Cláudio T. Silva; Juliana Freire (WWW, 2020)

From Closing Triangles to Closing Higher-Order Motifs. - Ryan A. Rossi; Anup Rao 002; Sungchul Kim; Eunyee Koh; Nesreen K. Ahmed (WWW (Companion Volume), 2020)

Fast and Accurate Estimation of Typed Graphlets. - Ryan A. Rossi; Anup Rao 002; Tung Mai; Nesreen K. Ahmed (WWW (Companion Volume), 2020)

Determinant-Preserving Sparsification of SDDM Matrices. - David Durfee; John Peebles; Richard Peng; Anup B. Rao (SIAM J. Comput., 2020)

Graph Neural Networks with Heterophily. - Jiong Zhu; Ryan A. Rossi; Anup Rao 002; Tung Mai; Nedim Lipka; Nesreen K. Ahmed; Danai Koutra (AAAI, 2021)

Efficient Balanced Treatment Assignments for Experimentation. - David Arbour; Drew Dimmery; Anup B. Rao (AISTATS, 2021)

Designing Transportable Experiments Under S-admissability. - My Phan; David Arbour; Drew Dimmery; Anup B. Rao (AISTATS, 2021)

From Closing Triangles to Higher-Order Motif Closures for Better Unsupervised Online Link Prediction. - Ryan A. Rossi; Anup B. Rao; Sungchul Kim; Eunyee Koh; Nesreen K. Ahmed; Gang Wu 013 (CIKM, 2021)

Machine Unlearning via Algorithmic Stability. - Enayat Ullah; Tung Mai; Anup Rao 002; Ryan A. Rossi; Raman Arora (COLT, 2021)

Fundamental Tradeoffs in Distributionally Adversarial Training. - Mohammad Mehrabi; Adel Javanmard; Ryan A. Rossi; Anup B. Rao; Tung Mai (ICML, 2021)

Asymptotics of Ridge Regression in Convolutional Models. - Mojtaba Sahraee-Ardakan; Tung Mai; Anup B. Rao; Ryan A. Rossi; Sundeep Rangan; Alyson K. Fletcher (ICML, 2021)

Interactive Audience Expansion On Large Scale Online Visitor Data. - Gromit Yeuk-Yin Chan; Tung Mai; Anup B. Rao; Ryan A. Rossi; Fan Du; Cláudio T. Silva; Juliana Freire (KDD, 2021)

Coresets for Classification - Simplified and Strengthened. - Tung Mai; Cameron Musco; Anup Rao 002 (NeurIPS, 2021)

Optimal Space and Time for Streaming Pattern Matching. - Tung Mai; Anup B. Rao; Ryan A. Rossi; Saeed Seddighin (CoRR, 2021)

Multiscale Manifold Warping. - Sridhar Mahadevan; Anup Rao 002; Georgios Theocharous; Jennifer Healey (CoRR, 2021)

An Interpretable Graph Generative Model with Heterophily. - Sudhanshu Chanpuriya; Ryan A. Rossi; Anup B. Rao; Tung Mai; Nedim Lipka; Zhao Song 002; Cameron Musco (CoRR, 2021)

Online MAP Inference and Learning for Nonsymmetric Determinantal Point Processes. - Aravind Reddy; Ryan A. Rossi; Zhao Song 002; Anup B. Rao; Tung Mai; Nedim Lipka; Gang Wu 013; Eunyee Koh; Nesreen K. Ahmed (CoRR, 2021)

Heterogeneous Graphlets. - Ryan A. Rossi; Nesreen K. Ahmed; Aldo G. Carranza; David Arbour; Anup B. Rao; Sungchul Kim; Eunyee Koh (ACM Trans. Knowl. Discov. Data, 2021)

Conditional Generative Model Based Predicate-Aware Query Approximation. - Nikhil Sheoran; Subrata Mitra; Vibhor Porwal; Siddharth Ghetia; Jatin Varshney; Tung Mai; Anup B. Rao; Vikas Maddukuri (AAAI, 2022)

Online Balanced Experimental Design. - David Arbour; Drew Dimmery; Tung Mai; Anup B. Rao (ICML, 2022)

One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes. - Aravind Reddy; Ryan A. Rossi; Zhao Song 002; Anup B. Rao; Tung Mai; Nedim Lipka; Gang Wu 013; Eunyee Koh; Nesreen K. Ahmed (ICML, 2022)

Sample Constrained Treatment Effect Estimation. - Raghavendra Addanki; David Arbour; Tung Mai; Cameron Musco; Anup Rao 002 (NeurIPS, 2022)

Efficient Insights Discovery through Conditional Generative Model based Query Approximation. - Vibhor Porwal; Subrata Mitra; Fan Du; John Anderson; Nikhil Sheoran; Anup B. Rao; Tung Mai; Gautam Kowshik; Sapthotharan Nair; Sameeksha Arora; Saurabh Mahapatra (SIGMOD Conference, 2022)

Electra: Conditional Generative Model based Predicate-Aware Query Approximation. - Nikhil Sheoran; Subrata Mitra; Vibhor Porwal; Siddharth Ghetia; Jatin Varshney; Tung Mai; Anup B. Rao; Vikas Maddukuri (CoRR, 2022)

Optimal Sketching Bounds for Sparse Linear Regression. - Tung Mai; Alexander Munteanu; Cameron Musco; Anup Rao 002; Chris Schwiegelshohn; David P. Woodruff (AISTATS, 2023)

Near Neighbor Search for Constraint Queries. - Gaurav Gupta; Anup B. Rao; Tung Mai; Ryan A. Rossi; Xiang Chen; Saayan Mitra; Anshumali Shrivastava (IEEE Big Data, 2023)

Decentralized Personalized Online Federated Learning. - Renzhi Wu; Saayan Mitra; Xiang Chen; Anup B. Rao (IEEE Big Data, 2023)

Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings. - Sudhanshu Chanpuriya; Ryan A. Rossi; Anup B. Rao; Tung Mai; Nedim Lipka; Zhao Song 002; Cameron Musco (NeurIPS, 2023)

Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation. - Mehrdad Ghadiri; David Arbour; Tung Mai; Cameron Musco; Anup B. Rao (NeurIPS, 2023)

Brief Announcement: Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. - Aniket Murhekar; David Arbour; Tung Mai; Anup B. Rao (SPAA, 2023)

Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. - Aniket Murhekar; David Arbour; Tung Mai; Anup Rao 002 (CoRR, 2023)

DeCoT: Debiasing Chain-of-Thought for Knowledge-Intensive Tasks in Large Language Models via Causal Intervention. - Junda Wu; Tong Yu 001; Xiang Chen; Haoliang Wang; Ryan A. Rossi; Sungchul Kim; Anup B. Rao; Julian J. McAuley (ACL (1), 2024)

RECON: Training-Free Acceleration for Text-to-Image Synthesis with Retrieval of Concept Prompt Trajectories. - Chen-Yi Lu; Shubham Agarwal 007; Md. Mehrab Tanjim; Kanak Mahadik; Anup B. Rao; Subrata Mitra; Shiv Kumar Saini; Saurabh Bagchi; Somali Chaterji (ECCV (59), 2024)

Hallucination Diversity-Aware Active Learning for Text Summarization. - Yu Xia 007; Xu Liu; Tong Yu 001; Sungchul Kim; Ryan A. Rossi; Anup B. Rao; Tung Mai; Shuai Li 010 (NAACL-HLT, 2024)

Evaluation and Incident Prevention in an Enterprise AI Assistant. - Akash V. Maharaj; David Arbour; Daniel Lee; Uttaran Bhattacharya; Anup B. Rao; Austin Zane; Avi Feller; Kun Qian 002; Yunyao Li 001 (AAAI, 2025)

On Distributional Discrepancy for Experimental Design with General Assignment Probabilities. - Anup Rao 002; Peng Zhang (AISTATS, 2025)

Learning to Clarify by Reinforcement Learning Through Reward-Weighted Fine-Tuning. - Subhojyoti Mukherjee; Viet Dac Lai; Raghavendra Addanki; Ryan A. Rossi; Seunghyun Yoon 002; Trung Bui; Anup B. Rao; Jayakumar Subramanian; Branislav Kveton (CoRR, 2025)