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ORCIDRavi Kumar 0001
S. Ravi Kumar 0001
Person information
- affiliation: Google
- affiliation: Yahoo! Research
- affiliation: IBM Almaden Research Center
- affiliation: Cornell University, Department of Computer Science
Other persons with the same name
- Ravi Kumar — disambiguation page
- Ravi Kumar 0002
![[0000-0001-9922-9064]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-9922-9064")
— Jaypee Institute of Engineering & Technology, India - Ravi Kumar 0004 — Department of Mechanical & Aerospace Engineering, University at Buffalo, Buffalo, NY, USA
- Ravi Kumar 0005 — Indian Institute of Information Technology, Kharagpur, India
- Ravi Kumar 0006 — Thapar University, Patiala, Punjab, India
- Ravi Kumar 0007 — Samsung Research Institute Delhi, India
- Ravi Kumar 0008 — CSIR-Institute of Microbial Technology, Chandigarh, India
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2020 – today
- 2022
[j58]Badih Ghazi, Ben Kreuter, Ravi Kumar, Pasin Manurangsi, Jiayu Peng, Evgeny Skvortsov, Yao Wang, Craig Wright:
Multiparty Reach and Frequency Histogram: Private, Secure, and Practical. Proc. Priv. Enhancing Technol. 2022(1): 373-395 (2022)- [c224]Nikhil Bansal, Christian Coester, Ravi Kumar, Manish Purohit, Erik Vee:
Learning-Augmented Weighted Paging. SODA 2022: 67-89 - [i42]Sungjin Im, Ravi Kumar, Aditya Petety, Manish Purohit:
Parsimonious Learning-Augmented Caching. CoRR abs/2202.04262 (2022) - [i41]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson:
Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. CoRR abs/2203.16476 (2022) - 2021
- [c223]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen:
Robust and Private Learning of Halfspaces. AISTATS 2021: 1603-1611 - [c222]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Power of Hints for Online Learning with Movement Costs. AISTATS 2021: 2818-2826 - [c221]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi:
Near-tight closure b ounds for the Littlestone and threshold dimensions. ALT 2021: 686-696 - [c220]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
On Avoiding the Union Bound When Answering Multiple Differentially Private Queries. COLT 2021: 2133-2146 - [c219]Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker:
On the Power of Multiple Anonymous Messages: Frequency Estimation and Selection in the Shuffle Model of Differential Privacy. EUROCRYPT (3) 2021: 463-488 - [c218]Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Locally Private k-Means in One Round. ICML 2021: 1441-1451 - [c217]Flavio Chierichetti, Ravi Kumar, Andrew Tomkins:
Light RUMs. ICML 2021: 1888-1897 - [c216]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha:
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message. ICML 2021: 3692-3701 - [c215]Lijie Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
On Distributed Differential Privacy and Counting Distinct Elements. ITCS 2021: 56:1-56:18 - [c214]Sungjin Im, Ravi Kumar, Mahshid Montazer Qaem, Manish Purohit:
Online Knapsack with Frequency Predictions. NeurIPS 2021: 2733-2743 - [c213]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
User-Level Differentially Private Learning via Correlated Sampling. NeurIPS 2021: 20172-20184 - [c212]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang:
Deep Learning with Label Differential Privacy. NeurIPS 2021: 27131-27145 - [c211]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Logarithmic Regret from Sublinear Hints. NeurIPS 2021: 28222-28232 - [c210]Sungjin Im, Ravi Kumar, Mahshid Montazer Qaem, Manish Purohit:
Non-Clairvoyant Scheduling with Predictions. SPAA 2021: 285-294 - [c209]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi:
Sample-efficient proper PAC learning with approximate differential privacy. STOC 2021: 183-196 - [i40]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang:
On Deep Learning with Label Differential Privacy. CoRR abs/2102.06062 (2021) - [i39]Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Locally Private k-Means in One Round. CoRR abs/2104.09734 (2021) - [i38]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh:
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead. CoRR abs/2106.04247 (2021) - [i37]Shailesh Bavadekar, Adam Boulanger, John Davis, Damien Desfontaines, Evgeniy Gabrilovich, Krishna Gadepalli, Badih Ghazi, Tague Griffith, Jai Prakash Gupta, Chaitanya Kamath, Dennis Kraft, Ravi Kumar, Akim Kumok, Yael Mayer, Pasin Manurangsi, Arti Patankar, Irippuge Milinda Perera, Chris Scott, Tomer Shekel, Benjamin Miller, Karen Smith, Charlotte Stanton, Mimi Sun, Mark Young, Gregory Wellenius:
Google COVID-19 Vaccination Search Insights: Anonymization Process Description. CoRR abs/2107.01179 (2021) - [i36]Rohan Anil, Badih Ghazi, Vineet Gupta, Ravi Kumar, Pasin Manurangsi:
Large-Scale Differentially Private BERT. CoRR abs/2108.01624 (2021) - [i35]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha:
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message. CoRR abs/2109.13158 (2021) - [i34]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
User-Level Private Learning via Correlated Sampling. CoRR abs/2110.11208 (2021) - [i33]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Logarithmic Regret from Sublinear Hints. CoRR abs/2111.05257 (2021) - [i32]Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Private Rank Aggregation in Central and Local Models. CoRR abs/2112.14652 (2021) - 2020
- [c208]Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian:
Fair Correlation Clustering. AISTATS 2020: 4195-4205 - [c207]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker:
Pure Differentially Private Summation from Anonymous Messages. ITC 2020: 15:1-15:23 - [c206]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Online Learning with Imperfect Hints. ICML 2020: 822-831 - [c205]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh:
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead. ICML 2020: 3505-3514 - [c204]Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Benjamin Moseley, Philip Pham, Sergei Vassilvitskii, Yuyan Wang:
Fair Hierarchical Clustering. NeurIPS 2020 - [c203]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Online Linear Optimization with Many Hints. NeurIPS 2020 - [c202]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Differentially Private Clustering: Tight Approximation Ratios. NeurIPS 2020 - [c201]Abhimanyu Das, Sreenivas Gollapudi, Ravi Kumar, Rina Panigrahy:
On the Learnability of Random Deep Networks. SODA 2020: 398-410 - [c200]Ravi Kumar, Manish Purohit, Zoya Svitkina, Erik Vee:
Interleaved Caching with Access Graphs. SODA 2020: 1846-1858 - [c199]Flavio Chierichetti, Ravi Kumar, Andrew Tomkins:
Asymptotic Behavior of Sequence Models. WWW 2020: 2824-2830 - [i31]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker:
Pure Differentially Private Summation from Anonymous Messages. CoRR abs/2002.01919 (2020) - [i30]Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian:
Fair Correlation Clustering. CoRR abs/2002.02274 (2020) - [i29]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Online Learning with Imperfect Hints. CoRR abs/2002.04726 (2020) - [i28]Andrei Z. Broder, Ravi Kumar:
A Note on Double Pooling Tests. CoRR abs/2004.01684 (2020) - [i27]Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Benjamin Moseley, Philip Pham, Sergei Vassilvitskii, Yuyan Wang:
Fair Hierarchical Clustering. CoRR abs/2006.10221 (2020) - [i26]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi:
Near-tight closure bounds for Littlestone and threshold dimensions. CoRR abs/2007.03668 (2020) - [i25]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
Differentially Private Clustering: Tight Approximation Ratios. CoRR abs/2008.08007 (2020) - [i24]Lijie Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
On Distributed Differential Privacy and Counting Distinct Elements. CoRR abs/2009.09604 (2020) - [i23]Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar:
On Additive Approximate Submodularity. CoRR abs/2010.02912 (2020) - [i22]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Online Linear Optimization with Many Hints. CoRR abs/2010.03082 (2020) - [i21]Nikhil Bansal, Christian Coester, Ravi Kumar, Manish Purohit, Erik Vee:
Scale-Free Allocation, Amortized Convexity, and Myopic Weighted Paging. CoRR abs/2011.09076 (2020) - [i20]Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen:
Robust and Private Learning of Halfspaces. CoRR abs/2011.14580 (2020) - [i19]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi:
Sample-efficient proper PAC learning with approximate differential privacy. CoRR abs/2012.03893 (2020) - [i18]Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
On Avoiding the Union Bound When Answering Multiple Differentially Private Queries. CoRR abs/2012.09116 (2020)
2010 – 2019
- 2019
- [j57]Flavio Chierichetti, Ravi Kumar, Alessandro Panconesi, Erisa Terolli:
On the Distortion of Locality Sensitive Hashing. SIAM J. Comput. 48(2): 350-372 (2019) - [c198]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii:
Matroids, Matchings, and Fairness. AISTATS 2019: 2212-2220 - [c197]Maryam Aliakbarpour, Ravi Kumar, Ronitt Rubinfeld:
Testing Mixtures of Discrete Distributions. COLT 2019: 83-114 - [c196]Ravi Kumar, Rina Panigrahy, Ali Rahimi, David P. Woodruff:
Faster Algorithms for Binary Matrix Factorization. ICML 2019: 3551-3559 - [c195]Ravi Kumar, Manish Purohit, Aaron Schild, Zoya Svitkina, Erik Vee:
Semi-Online Bipartite Matching. ITCS 2019: 50:1-50:20 - [c194]Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian:
Clustering without Over-Representation. KDD 2019: 267-275 - [c193]Neha Arora, James Cook, Ravi Kumar, Ivan Kuznetsov, Yechen Li, Huai-Jen Liang, Andrew Miller, Andrew Tomkins, Iveel Tsogsuren, Yi Wang:
Hard to Park?: Estimating Parking Difficulty at Scale. KDD 2019: 2296-2304 - [c192]Ravi Kumar, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang:
Efficient Rematerialization for Deep Networks. NeurIPS 2019: 15146-15155 - [i17]Abhimanyu Das, Sreenivas Gollapudi, Ravi Kumar, Rina Panigrahy:
On the Learnability of Deep Random Networks. CoRR abs/1904.03866 (2019) - [i16]Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian:
Clustering without Over-Representation. CoRR abs/1905.12753 (2019) - [i15]Maryam Aliakbarpour, Ravi Kumar, Ronitt Rubinfeld:
Testing Mixtures of Discrete Distributions. CoRR abs/1907.03190 (2019) - [i14]Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker:
Private Heavy Hitters and Range Queries in the Shuffled Model. CoRR abs/1908.11358 (2019) - [i13]Benjamin Spector, Ravi Kumar, Andrew Tomkins:
Preventing Adversarial Use of Datasets through Fair Core-Set Construction. CoRR abs/1910.10871 (2019) - [i12]Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker:
On the Power of Multiple Anonymous Messages. IACR Cryptol. ePrint Arch. 2019: 1382 (2019) - 2018
- [j56]Marco Bressan, Flavio Chierichetti, Ravi Kumar, Stefano Leucci, Alessandro Panconesi:
Motif Counting Beyond Five Nodes. ACM Trans. Knowl. Discov. Data 12(4): 48:1-48:25 (2018) - [c191]Flavio Chierichetti, Ravi Kumar, Andrew Tomkins:
Learning a Mixture of Two Multinomial Logits. ICML 2018: 960-968 - [c190]Austin R. Benson, Ravi Kumar, Andrew Tomkins:
Sequences of Sets. KDD 2018: 1148-1157 - [c189]Flavio Chierichetti, Anirban Dasgupta, Shahrzad Haddadan, Ravi Kumar, Silvio Lattanzi:
Mallows Models for Top-k Lists. NeurIPS 2018: 4387-4397 - [c188]Manish Purohit, Zoya Svitkina, Ravi Kumar:
Improving Online Algorithms via ML Predictions. NeurIPS 2018: 9684-9693 - [c187]Flavio Chierichetti, Ravi Kumar, Andrew Tomkins:
Discrete Choice, Permutations, and Reconstruction. SODA 2018: 576-586 - [c186]Austin R. Benson, Ravi Kumar, Andrew Tomkins:
A Discrete Choice Model for Subset Selection. WSDM 2018: 37-45 - [r2]Ravi Kumar:
Web Page Quality Metrics. Encyclopedia of Database Systems (2nd ed.) 2018 - [i11]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii:
Fair Clustering Through Fairlets. CoRR abs/1802.05733 (2018) - [i10]Ravi Kumar, Manish Purohit, Aaron Schild, Zoya Svitkina, Erik Vee:
Semi-Online Bipartite Matching. CoRR abs/1812.00134 (2018) - 2017
- [j55]Shalmoli Gupta, Ravi Kumar, Kefu Lu, Benjamin Moseley, Sergei Vassilvitskii:
Local Search Methods for k-Means with Outliers. Proc. VLDB Endow. 10(7): 757-768 (2017) - [c185]Sreenivas Gollapudi, Ravi Kumar, Debmalya Panigrahi, Rina Panigrahy:
Partitioning Orders in Online Shopping Services. CIKM 2017: 1319-1328 - [c184]Flavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar, Silvio Lattanzi, Rina Panigrahy, David P. Woodruff:
Algorithms for $\ell_p$ Low-Rank Approximation. ICML 2017: 806-814 - [c183]Flavio Chierichetti, Ravi Kumar, Alessandro Panconesi, Erisa Terolli:
The Distortion of Locality Sensitive Hashing. ITCS 2017: 54:1-54:18 - [c182]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii:
Fair Clustering Through Fairlets. NIPS 2017: 5029-5037 - [c181]Flavio Chierichetti, Ravi Kumar, Bo Pang:
On the Power Laws of Language: Word Frequency Distributions. SIGIR 2017: 385-394 - [c180]Marco Bressan, Flavio Chierichetti, Ravi Kumar, Stefano Leucci, Alessandro Panconesi:
Counting Graphlets: Space vs Time. WSDM 2017: 557-566 - [c179]Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins:
Linear Additive Markov Processes. WWW 2017: 411-419 - [c178]Anirban Dasgupta, Ravi Kumar, Tamás Sarlós:
Caching with Dual Costs. WWW (Companion Volume) 2017: 643-652 - [i9]Ravi Kumar, Maithra Raghu, Tamás Sarlós, Andrew Tomkins:
Linear Additive Markov Processes. CoRR abs/1704.01255 (2017) - [i8]Flavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar, Silvio Lattanzi, Rina Panigrahy, David P. Woodruff:
Algorithms for $\ell_p$ Low Rank Approximation. CoRR abs/1705.06730 (2017) - 2016
- [j54]Naren Ramakrishnan, Ravi Kumar:
Big Data. Computer 49(4): 20-22 (2016) - [j53]Ronald Fagin, Ravi Kumar, Mohammad Mahdian, D. Sivakumar, Erik Vee:
An Algorithmic View of Voting. SIAM J. Discret. Math. 30(4): 1978-1996 (2016) - [j52]Lawrence B. Holder, Rajmonda Sulo Caceres, David F. Gleich, E. Jason Riedy, Maleq Khan, Nitesh V. Chawla, Ravi Kumar, Yinghui Wu, Christine Klymko, Tina Eliassi-Rad, B. Aditya Prakash:
Current and Future Challenges in Mining Large Networks: Report on the Second SDM Workshop on Mining Networks and Graphs. SIGKDD Explor. 18(1): 39-45 (2016) - [c177]Amirali Abdullah, Ravi Kumar, Andrew McGregor, Sergei Vassilvitskii, Suresh Venkatasubramanian:
Sketching, Embedding and Dimensionality Reduction in Information Theoretic Spaces. AISTATS 2016: 948-956 - [c176]Ravi Kumar:
Sequences, Choices, and their Dynamics. COMAD 2016 - [c175]Justine Zhang, Ravi Kumar, Sujith Ravi, Cristian Danescu-Niculescu-Mizil:
Conversational Flow in Oxford-style Debates. HLT-NAACL 2016: 136-141 - [c174]Rishi Gupta, Ravi Kumar, Sergei Vassilvitskii:
On Mixtures of Markov Chains. NIPS 2016: 3441-3449 - [c173]Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi, Tamás Sarlós:
On Sampling Nodes in a Network. WWW 2016: 471-481 - [c172]Austin R. Benson, Ravi Kumar, Andrew Tomkins:
Modeling User Consumption Sequences. WWW 2016: 519-529 - [c171]Austin R. Benson, Ravi Kumar, Andrew Tomkins:
On the Relevance of Irrelevant Alternatives. WWW 2016: 963-973 - [e8]Ravi Kumar, James Caverlee, Hanghang Tong:
2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016, San Francisco, CA, USA, August 18-21, 2016. IEEE Computer Society 2016, ISBN 978-1-5090-2846-7 [contents] - [i7]Justine Zhang, Ravi Kumar, Sujith Ravi, Cristian Danescu-Niculescu-Mizil:
Conversational flow in Oxford-style debates. CoRR abs/1604.03114 (2016) - 2015
- [j51]Flavio Chierichetti, Ravi Kumar:
LSH-Preserving Functions and Their Applications. J. ACM 62(5): 33:1-33:25 (2015) - [j50]Ravi Kumar, Benjamin Moseley, Sergei Vassilvitskii, Andrea Vattani:
Fast Greedy Algorithms in MapReduce and Streaming. ACM Trans. Parallel Comput. 2(3): 14:1-14:22 (2015) - [c170]Song Feng, Sujith Ravi, Ravi Kumar, Polina Kuznetsova, Wei Liu, Alexander C. Berg, Tamara L. Berg, Yejin Choi:
Refer-to-as Relations as Semantic Knowledge. AAAI 2015: 2160-2166 - [c169]Flavio Chierichetti, Abhimanyu Das, Anirban Dasgupta, Ravi Kumar:
Approximate Modularity. FOCS 2015: 1143-1162 - [c168]Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi:
On Learning Mixture Models for Permutations. ITCS 2015: 85-92 - [c167]Flavio Chierichetti, Alessandro Epasto, Ravi Kumar, Silvio Lattanzi, Vahab S. Mirrokni:
Efficient Algorithms for Public-Private Social Networks. KDD 2015: 139-148 - [c166]Ravi Kumar, Mohammad Mahdian, Bo Pang, Andrew Tomkins, Sergei Vassilvitskii:
Driven by Food: Modeling Geographic Choice. WSDM 2015: 213-222 - [c165]Ravi Kumar, Andrew Tomkins, Sergei Vassilvitskii, Erik Vee:
Inverting a Steady-State. WSDM 2015: 359-368 - [e7]James Bailey, Alistair Moffat, Charu C. Aggarwal, Maarten de Rijke, Ravi Kumar, Vanessa Murdock, Timos K. Sellis, Jeffrey Xu Yu:
Proceedings of the 24th ACM International Conference on Information and Knowledge Management, CIKM 2015, Melbourne, VIC, Australia, October 19 - 23, 2015. ACM 2015, ISBN 978-1-4503-3794-6 [contents] - [i6]Amirali Abdullah, Ravi Kumar, Andrew McGregor, Sergei Vassilvitskii, Suresh Venkatasubramanian:
Sketching, Embedding, and Dimensionality Reduction for Information Spaces. CoRR abs/1503.05225 (2015) - 2014
- [j49]Flavio Chierichetti, Ravi Kumar, Mohammad Mahdian:
The complexity of LSH feasibility. Theor. Comput. Sci. 530: 89-101 (2014) - [c164]Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi:
On Reconstructing a Hidden Permutation. APPROX-RANDOM 2014: 604-617 - [c163]Flavio Chierichetti, Jon M. Kleinberg, Ravi Kumar, Mohammad Mahdian, Sandeep Pandey:
Event Detection via Communication Pattern Analysis. ICWSM 2014 - [c162]Sujith Ravi, Bo Pang, Vibhor Rastogi, Ravi Kumar:
Great Question! Question Quality in Community Q&A. ICWSM 2014 - [c161]Flavio Chierichetti, Nilesh N. Dalvi, Ravi Kumar:
Correlation clustering in MapReduce. KDD 2014: 641-650 - [c160]Flavio Chierichetti, Anirban Dasgupta, Ravi Kumar, Silvio Lattanzi:
Learning Entangled Single-Sample Gaussians. SODA 2014: 511-522 - [c159]Ashton Anderson, Ravi Kumar, Andrew Tomkins, Sergei Vassilvitskii:
The dynamics of repeat consumption. WWW 2014: 419-430 - [c158]Anirban Dasgupta, Ravi Kumar, Tamás Sarlós:
On estimating the average degree. WWW 2014: 795-806 - [e6]Ravi Kumar, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, Xindong Wu:
2014 IEEE International Conference on Data Mining, ICDM 2014, Shenzhen, China, December 14-17, 2014. IEEE Computer Society 2014, ISBN 978-1-4799-4302-9 [contents] - [e5]Zhi-Hua Zhou, Wei Wang, Ravi Kumar, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, Xindong Wu:
2014 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2014, Shenzhen, China, December 14, 2014. IEEE Computer Society 2014, ISBN 978-1-4799-4274-9 [contents] - 2013
- [j48]Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Alessandro Panconesi, Prabhakar Raghavan:
Models for the Compressible Web. SIAM J. Comput. 42(5): 1777-1802 (2013) - [c157]Anirban Dasgupta, Ravi Kumar, Sujith Ravi:
Summarization Through Submodularity and Dispersion. ACL (1) 2013: 1014-1022 - [c156]Ravi Kumar, Daniel Lokshtanov, Sergei Vassilvitskii, Andrea Vattani:
Near-Optimal Bounds for Cross-Validation via Loss Stability. ICML (1) 2013: 27-35 - [c155]Nilesh N. Dalvi, Ravi Kumar, Bo Pang:
Para 'Normal' Activity: On the Distribution of Average Ratings. ICWSM 2013 - [c154]Ravi Kumar, Benjamin Moseley, Sergei Vassilvitskii, Andrea Vattani:
Fast greedy algorithms in mapreduce and streaming. SPAA 2013: 1-10 - [c153]Ravi Kumar, Ronny Lempel, Roy Schwartz, Sergei Vassilvitskii:
Rank quantization.