Krishnaram Kenthapadi

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 83

Top Venues

CoRR

KDD

CIKM

WWW (Companion Volume)

Publications

Krishnaram Kenthapadi, Mehrnoosh Sameki, Ankur Taly
Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey). KDD (2024)
Krishnaram Kenthapadi, Mehrnoosh Sameki, Ankur Taly
Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey). CoRR (2024)
Krishnaram Kenthapadi, Himabindu Lakkaraju, Nazneen Rajani
Generative AI meets Responsible AI: Practical Challenges and Opportunities. KDD (2023)
Vijay Keswani, L. Elisa Celis, Krishnaram Kenthapadi, Matthew Lease
Designing Closed-Loop Models for Task Allocation. CoRR (2023)
Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu
Tutorials at The Web Conference 2023. WWW (Companion Volume) (2023)
Vijay Keswani, L. Elisa Celis, Krishnaram Kenthapadi, Matthew Lease
Designing Closed-Loop Models for Task Allocation. HHAI (2023)
Gyandev Gupta, Bashir Rastegarpanah, Amalendu Iyer, Joshua Rubin, Krishnaram Kenthapadi
Measuring Distributional Shifts in Text: The Advantage of Language Model-Based Embeddings. CoRR (2023)
Kate Donahue, Alexandra Chouldechova, Krishnaram Kenthapadi
Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness. CoRR (2022)
Matthäus Kleindessner, Samira Samadi, Muhammad Bilal Zafar, Krishnaram Kenthapadi, Chris Russell
Pairwise Fairness for Ordinal Regression. AISTATS (2022)
Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. NeurIPS (2022)
Murtuza N. Shergadwala, Himabindu Lakkaraju, Krishnaram Kenthapadi
A Human-Centric Take on Model Monitoring. CoRR (2022)
Fan Wu, Linyi Li, Huan Zhang, Bhavya Kailkhura, Krishnaram Kenthapadi, Ding Zhao, Bo Li
COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks. ICLR (2022)
Nathalie Rauschmayr, Sami Kama, Muhyun Kim, Miyoung Choi, Krishnaram Kenthapadi
Profiling Deep Learning Workloads at Scale using Amazon SageMaker. KDD (2022)
Emily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth, Saeed Sharifi-Malvajerdi
Multiaccurate Proxies for Downstream Fairness. FAccT (2022)
Fan Wu, Linyi Li, Chejian Xu, Huan Zhang, Bhavya Kailkhura, Krishnaram Kenthapadi, Ding Zhao, Bo Li
COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks. CoRR (2022)
David Munechika, Zijie J. Wang, Jack Reidy, Joshua Rubin, Krishna Gade, Krishnaram Kenthapadi, Duen Horng Chau
Visual Auditor: Interactive Visualization for Detection and Summarization of Model Biases. IEEE VIS (Short Papers) (2022)
Vijay Keswani, Matthew Lease, Krishnaram Kenthapadi
Designing Closed Human-in-the-loop Deferral Pipelines. CoRR (2022)
Murtuza N. Shergadwala, Himabindu Lakkaraju, Krishnaram Kenthapadi
A Human-Centric Perspective on Model Monitoring. HCOMP (2022)
David Nigenda, Zohar Karnin, Muhammad Bilal Zafar, Raghu Ramesha, Alan Tan, Michele Donini, Krishnaram Kenthapadi
Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models. KDD (2022)
Krishnaram Kenthapadi, Himabindu Lakkaraju, Pradeep Natarajan, Mehrnoosh Sameki
Model Monitoring in Practice: Lessons Learned and Open Challenges. KDD (2022)
Déborah Sulem, Michele Donini, Muhammad Bilal Zafar, Francois-Xavier Aubet, Jan Gasthaus, Tim Januschowski, Sanjiv Das, Krishnaram Kenthapadi, Cédric Archambeau
Diverse Counterfactual Explanations for Anomaly Detection in Time Series. CoRR (2022)
David Munechika, Zijie J. Wang, Jack Reidy, Josh Rubin, Krishna Gade, Krishnaram Kenthapadi, Duen Horng Chau
Visual Auditor: Interactive Visualization for Detection and Summarization of Model Biases. CoRR (2022)
Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. CoRR (2022)
Kate Donahue, Alexandra Chouldechova, Krishnaram Kenthapadi
Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness. FAccT (2022)
Ana Lucic, Sheeraz Ahmad, Amanda Furtado Brinhosa, Vera Liao, Himani Agrawal, Umang Bhatt, Krishnaram Kenthapadi, Alice Xiang, Maarten de Rijke, Nicholas Drabowski
Towards the Use of Saliency Maps for Explaining Low-Quality Electrocardiograms to End Users. CoRR (2022)
Yigitcan Kaya, Muhammad Bilal Zafar, Sergül Aydöre, Nathalie Rauschmayr, Krishnaram Kenthapadi
Generating Distributional Adversarial Examples to Evade Statistical Detectors. ICML (2022)
Muhammad Bilal Zafar, Michele Donini, Dylan Slack, Cédric Archambeau, Sanjiv Das, Krishnaram Kenthapadi
On the Lack of Robust Interpretability of Neural Text Classifiers. CoRR (2021)
Vijay Keswani, Matthew Lease, Krishnaram Kenthapadi
Towards Unbiased and Accurate Deferral to Multiple Experts. CoRR (2021)
Michaela Hardt, Xiaoguang Chen, Xiaoyi Cheng, Michele Donini, Jason Gelman, Satish Gollaprolu, John He, Pedro Larroy, Xinyu Liu, Nick McCarthy, Ashish Rathi, Scott Rees, Ankit A. Siva, ErhYuan Tsai, Keerthan Vasist, Pinar Yilmaz, Muhammad Bilal Zafar, Sanjiv Das, Kevin Haas, Tyler Hill, Krishnaram Kenthapadi
Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud. CoRR (2021)
Valerio Perrone, Huibin Shen, Aida Zolic, Iaroslav Shcherbatyi, Amr Ahmed, Tanya Bansal, Michele Donini, Fela Winkelmolen, Rodolphe Jenatton, Jean Baptiste Faddoul, Barbara Pogorzelska, Miroslav Miladinovic, Krishnaram Kenthapadi, Matthias W. Seeger, Cédric Archambeau
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization. KDD (2021)
Zeinab S. Jalali, Krishnaram Kenthapadi, Sucheta Soundarajan
On Measuring the Diversity of Organizational Networks. CoRR (2021)
Michaela Hardt, Xiaoguang Chen, Xiaoyi Cheng, Michele Donini, Jason Gelman, Satish Gollaprolu, John He, Pedro Larroy, Xinyu Liu, Nick McCarthy, Ashish Rathi, Scott Rees, Ankit A. Siva, ErhYuan Tsai, Keerthan Vasist, Pinar Yilmaz, Muhammad Bilal Zafar, Sanjiv Das, Kevin Haas, Tyler Hill, Krishnaram Kenthapadi
Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud. KDD (2021)
Vijay Keswani, Matthew Lease, Krishnaram Kenthapadi
Towards Unbiased and Accurate Deferral to Multiple Experts. AIES (2021)
Sergül Aydöre, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Ankit A. Siva
Differentially Private Query Release Through Adaptive Projection. ICML (2021)
Emily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth, Saeed Sharifi-Malvajerdi
Multiaccurate Proxies for Downstream Fairness. CoRR (2021)
David Nigenda, Zohar Karnin, Muhammad Bilal Zafar, Raghu Ramesha, Alan Tan, Michele Donini, Krishnaram Kenthapadi
Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models. CoRR (2021)
Matthäus Kleindessner, Samira Samadi, Muhammad Bilal Zafar, Krishnaram Kenthapadi, Chris Russell
Pairwise Fairness for Ordinal Regression. CoRR (2021)
Nathalie Rauschmayr, Vikas Kumar, Rahul Huilgol, Andrea Olgiati, Satadal Bhattacharjee, Nihal Harish, Vandana Kannan, Amol Lele, Anirudh Acharya, Jared Nielsen, Lakshmi Ramakrishnan, Ishan Bhatt, Kohen Chia, Neelesh Dodda, Zhihan Li, Jiacheng Gu, Miyoung Choi, Balajee Nagarajan, Jeffrey Geevarghese, Denis Davydenko, Sifei Li, Lu Huang, Edward Kim, Tyler Hill, Krishnaram Kenthapadi
Amazon SageMaker Debugger: A System for Real-Time Insights into Machine Learning Model Training. MLSys (2021)
Valerio Perrone, Michele Donini, Muhammad Bilal Zafar, Robin Schmucker, Krishnaram Kenthapadi, Cédric Archambeau
Fair Bayesian Optimization. AIES (2021)
Sergül Aydöre, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Ankit A. Siva
Differentially Private Query Release Through Adaptive Projection. CoRR (2021)
Emily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth
Minimax Group Fairness: Algorithms and Experiments. AIES (2021)
Muhammad Bilal Zafar, Michele Donini, Dylan Slack, Cédric Archambeau, Sanjiv Das, Krishnaram Kenthapadi
On the Lack of Robust Interpretability of Neural Text Classifiers. ACL/IJCNLP (Findings) (2021)
Muhammad Bilal Zafar, Philipp Schmidt, Michele Donini, Cédric Archambeau, Felix Biessmann, Sanjiv Ranjan Das, Krishnaram Kenthapadi
More Than Words: Towards Better Quality Interpretations of Text Classifiers. CoRR (2021)
Dylan Slack, Nathalie Rauschmayr, Krishnaram Kenthapadi
Defuse: Harnessing Unrestricted Adversarial Examples for Debugging Models Beyond Test Accuracy. CoRR (2021)
Valerio Perrone, Huibin Shen, Aida Zolic, Iaroslav Shcherbatyi, Amr Ahmed, Tanya Bansal, Michele Donini, Fela Winkelmolen, Rodolphe Jenatton, Jean Baptiste Faddoul, Barbara Pogorzelska, Miroslav Miladinovic, Krishnaram Kenthapadi, Matthias W. Seeger, Cédric Archambeau
Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization. CoRR (2020)
Sriram Vasudevan, Krishnaram Kenthapadi
LiFT: A Scalable Framework for Measuring Fairness in ML Applications. CoRR (2020)
G. Roshan Lal, Sahin Cem Geyik, Krishnaram Kenthapadi
Fairness-Aware Online Personalization. CoRR (2020)
Sriram Vasudevan, Krishnaram Kenthapadi
LiFT: A Scalable Framework for Measuring Fairness in ML Applications. CIKM (2020)
Krishna Gade, Sahin Cem Geyik, Krishnaram Kenthapadi, Varun Mithal, Ankur Taly
Explainable AI in industry: practical challenges and lessons learned: implications tutorial. FAT* (2020)
Cyrus DiCiccio, Sriram Vasudevan, Kinjal Basu, Krishnaram Kenthapadi, Deepak Agarwal
Evaluating Fairness Using Permutation Tests. KDD (2020)
Kathy Baxter, Yoav Schlesinger, Sarah Aerni, Lewis Baker, Julie Dawson, Krishnaram Kenthapadi, Isabel M. Kloumann, Hanna M. Wallach
Bridging the gap from AI ethics research to practice. FAT* (2020)
Krishna Gade, Sahin Cem Geyik, Krishnaram Kenthapadi, Varun Mithal, Ankur Taly
Explainable AI in Industry: Practical Challenges and Lessons Learned. WWW (Companion Volume) (2020)
Valerio Perrone, Michele Donini, Krishnaram Kenthapadi, Cédric Archambeau
Fair Bayesian Optimization. CoRR (2020)
Emily Diana, Wesley Gill, Michael Kearns, Krishnaram Kenthapadi, Aaron Roth
Convergent Algorithms for (Relaxed) Minimax Fairness. CoRR (2020)
Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. CoRR (2019)
Sarah Bird, Ben Hutchinson, Krishnaram Kenthapadi, Emre Kiciman, Margaret Mitchell
Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned. KDD (2019)
Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Kalai
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. NAACL-HLT (1) (2019)
Sarah Bird, Krishnaram Kenthapadi, Emre Kiciman, Margaret Mitchell
Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned. WSDM (2019)
Sarah Bird, Ben Hutchinson, Krishnaram Kenthapadi, Emre Kiciman, Margaret Mitchell
Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned. WWW (Companion Volume) (2019)
Sahin Cem Geyik, Stuart Ambler, Krishnaram Kenthapadi
Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search. KDD (2019)
Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. FAT (2019)
Sahin Cem Geyik, Stuart Ambler, Krishnaram Kenthapadi
Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search. CoRR (2019)
Krishna Gade, Sahin Cem Geyik, Krishnaram Kenthapadi, Varun Mithal, Ankur Taly
Explainable AI in Industry. KDD (2019)
Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. CoRR (2019)
Krishnaram Kenthapadi, Ilya Mironov, Abhradeep Guha Thakurta
Privacy-preserving Data Mining in Industry. WSDM (2019)
Krishnaram Kenthapadi, Ilya Mironov, Abhradeep Thakurta
Privacy-preserving Data Mining in Industry. WWW (Companion Volume) (2019)
Sahin Cem Geyik, Qi Guo, Bo Hu, Cagri Ozcaglar, Ketan Thakkar, Xianren Wu, Krishnaram Kenthapadi
Talent Search and Recommendation Systems at LinkedIn: Practical Challenges and Lessons Learned. CoRR (2018)
Rohan Ramanath, Hakan Inan, Gungor Polatkan, Bo Hu, Qi Guo, Cagri Ozcaglar, Xianren Wu, Krishnaram Kenthapadi, Sahin Cem Geyik
Towards Deep and Representation Learning for Talent Search at LinkedIn. CoRR (2018)
Xi Chen, Yiqun Liu, Liang Zhang, Krishnaram Kenthapadi
How LinkedIn Economic Graph Bonds Information and Product: Applications in LinkedIn Salary. CoRR (2018)
Rohan Ramanath, Hakan Inan, Gungor Polatkan, Bo Hu, Qi Guo, Cagri Ozcaglar, Xianren Wu, Krishnaram Kenthapadi, Sahin Cem Geyik
Towards Deep and Representation Learning for Talent Search at LinkedIn. CIKM (2018)
Sahin Cem Geyik, Qi Guo, Bo Hu, Cagri Ozcaglar, Ketan Thakkar, Xianren Wu, Krishnaram Kenthapadi
Talent Search and Recommendation Systems at LinkedIn: Practical Challenges and Lessons Learned. SIGIR (2018)
Krishnaram Kenthapadi, Thanh T. L. Tran
PriPeARL: A Framework for Privacy-Preserving Analytics and Reporting at LinkedIn. CoRR (2018)
Xi Chen, Yiqun Liu, Liang Zhang, Krishnaram Kenthapadi
How LinkedIn Economic Graph Bonds Information and Product: Applications in LinkedIn Salary. KDD (2018)
Krishnaram Kenthapadi, Thanh T. L. Tran
PriPeARL: A Framework for Privacy-Preserving Analytics and Reporting at LinkedIn. CIKM (2018)
Dhruv Arya, Ganesh Venkataraman, Aman Grover, Krishnaram Kenthapadi
Candidate Selection for Large Scale Personalized Search and Recommender Systems. SIGIR (2017)
Krishnaram Kenthapadi, Stuart Ambler, Liang Zhang, Deepak Agarwal
Bringing Salary Transparency to the World: Computing Robust Compensation Insights via LinkedIn Salary. CoRR (2017)
Krishnaram Kenthapadi, Ahsan Chudhary, Stuart Ambler
LinkedIn Salary: A System for Secure Collection and Presentation of Structured Compensation Insights to Job Seekers. PAC (2017)
Krishnaram Kenthapadi, Benjamin Le, Ganesh Venkataraman
Personalized Job Recommendation System at LinkedIn: Practical Challenges and Lessons Learned. RecSys (2017)
Krishnaram Kenthapadi, Ahsan Chudhary, Stuart Ambler
LinkedIn Salary: A System for Secure Collection and Presentation of Structured Compensation Insights to Job Seekers. CoRR (2017)
Krishnaram Kenthapadi, Stuart Ambler, Liang Zhang, Deepak Agarwal
Bringing Salary Transparency to the World: Computing Robust Compensation Insights via LinkedIn Salary. CIKM (2017)
Jian Wang, Krishnaram Kenthapadi, Kaushik Rangadurai, David Hardtke
Dionysius: A Framework for Modeling Hierarchical User Interactions in Recommender Systems. CoRR (2017)
Fedor Borisyuk, Liang Zhang, Krishnaram Kenthapadi
LiJAR: A System for Job Application Redistribution towards Efficient Career Marketplace. KDD (2017)
Fedor Borisyuk, Krishnaram Kenthapadi, David Stein, Bo Zhao
CaSMoS: A Framework for Learning Candidate Selection Models over Structured Queries and Documents. KDD (2016)
Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi
Similarity Search using Concept Graphs. CIKM (2014)
Rakesh Agrawal, M. Hanif Jhaveri, Krishnaram Kenthapadi
Evaluating educational interventions at scale. L@S (2014)
Marios Kokkodis, Anitha Kannan, Krishnaram Kenthapadi
Assigning Educational Videos at Appropriate Locations in Textbooks. EDM (2014)
Marios Kokkodis, Anitha Kannan, Krishnaram Kenthapadi
Assigning videos to textbooks at appropriate granularity. L@S (2014)
James Cook, Abhimanyu Das, Krishnaram Kenthapadi, Nina Mishra
Ranking Twitter discussion groups. COSN (2014)
Rakesh Agrawal, Maria Christoforaki, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi, Adith Swaminathan
Mining Videos from the Web for Electronic Textbooks. ICFCA (2014)
Krishnaram Kenthapadi, Nina Mishra, Kobbi Nissim
Denials leak information: Simulatable auditing. J. Comput. Syst. Sci. 79 (8) (2013)
Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi
Studying from electronic textbooks. CIKM (2013)
Krishnaram Kenthapadi, Aleksandra Korolova, Ilya Mironov, Nina Mishra
Privacy via the Johnson-Lindenstrauss Transform. J. Priv. Confidentiality 5 (1) (2013)
James Cook, Krishnaram Kenthapadi, Nina Mishra
Group chats on Twitter. WWW (2013)
Rakesh Agrawal, Sunandan Chakraborty, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi
Quality of textbooks: an empirical study. ACM DEV (2012)
Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi
Electronic Textbooks and Data Mining. WAIM (2012)
Rakesh Agrawal, Sunandan Chakraborty, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi
Empowering authors to diagnose comprehension burden in textbooks. KDD (2012)
Krishnaram Kenthapadi, Aleksandra Korolova, Ilya Mironov, Nina Mishra
Privacy via the Johnson-Lindenstrauss Transform CoRR (2012)
Marc Najork, Dennis Fetterly, Alan Halverson, Krishnaram Kenthapadi, Sreenivas Gollapudi
Of hammers and nails: an empirical comparison of three paradigms for processing large graphs. WSDM (2012)
Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi
Enriching Education through Data Mining. PReMI (2011)
Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi
Data mining for improving textbooks. SIGKDD Explor. 13 (2) (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Krishnaram Kenthapadi