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ORCIDMoses Charikar
Moses Samson Charikar
Person information
- affiliation: Princeton University
- award (2012): Paris Kanellakis Award
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2020 – today
- 2023
[c131]Soheil Behnezhad, Moses Charikar, Weiyun Ma, Li-Yang Tan:
Single-Pass Streaming Algorithms for Correlation Clustering. SODA 2023: 819-849- [c130]Moses Charikar, Chirag Pabbaraju:
A Characterization of List Learnability. STOC 2023: 1713-1726 - [i60]Nima Anari, Moses Charikar, Prasanna Ramakrishnan:
Distortion in metric matching with ordinal preferences. CoRR abs/2305.12119 (2023) - 2022
- [c129]Soheil Behnezhad, Moses Charikar, Weiyun Ma, Li-Yang Tan:
Almost 3-Approximate Correlation Clustering in Constant Rounds. FOCS 2022: 720-731 - [c128]Moses Charikar, Erik Waingarten:
Polylogarithmic Sketches for Clustering. ICALP 2022: 38:1-38:20 - [c127]Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford:
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. NeurIPS 2022 - [c126]Moses Charikar, Lunjia Hu:
Near-Optimal Explainable k-Means for All Dimensions. SODA 2022: 2580-2606 - [c125]Moses Charikar, Prasanna Ramakrishnan:
Metric Distortion Bounds for Randomized Social Choice. SODA 2022: 2986-3004 - [i59]Moses Charikar, Erik Waingarten:
Polylogarithmic Sketches for Clustering. CoRR abs/2204.12358 (2022) - [i58]Moses Charikar, Erik Waingarten:
The Johnson-Lindenstrauss Lemma for Clustering and Subspace Approximation: From Coresets to Dimension Reduction. CoRR abs/2205.00371 (2022) - [i57]Soheil Behnezhad, Moses Charikar, Weiyun Ma, Li-Yang Tan:
Almost 3-Approximate Correlation Clustering in Constant Rounds. CoRR abs/2205.03710 (2022) - [i56]Moses Charikar, Paul Liu, Tianyu Liu, Thuy-Duong Vuong:
On the Complexity of Sampling Redistricting Plans. CoRR abs/2206.04883 (2022) - [i55]Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford:
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. CoRR abs/2210.06728 (2022) - [i54]Moses Charikar, Chirag Pabbaraju:
A Characterization of List Learnability. CoRR abs/2211.04956 (2022) - 2021
- [c124]Moses Charikar, Lunjia Hu:
Approximation Algorithms for Orthogonal Non-negative Matrix Factorization. AISTATS 2021: 2728-2736 - [c123]Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood. COLT 2021: 93-158 - [c122]Guy Blanc, Moses Charikar:
Multiway Online Correlated Selection. FOCS 2021: 1277-1284 - [c121]Moses Charikar, Shivam Garg, Deborah M. Gordon, Kirankumar Shiragur:
A Model for Ant Trail Formation and its Convergence Properties (Extended Abstract). ITCS 2021: 85:1-85:2 - [c120]Moses Charikar, Weiyun Ma, Li-Yang Tan:
Brief Announcement: A Randomness-efficient Massively Parallel Algorithm for Connectivity. PODC 2021: 431-433 - [c119]Moses Charikar, Paul Liu:
Improved Algorithms for Edge Colouring in the W-Streaming Model. SOSA 2021: 181-183 - [i53]Moses Charikar, Lunjia Hu:
Approximation Algorithms for Orthogonal Non-negative Matrix Factorization. CoRR abs/2103.01398 (2021) - [i52]Guy Blanc, Moses Charikar:
Multiway Online Correlated Selection. CoRR abs/2106.05579 (2021) - [i51]Moses Charikar, Lunjia Hu:
Near-Optimal Explainable k-Means for All Dimensions. CoRR abs/2106.15566 (2021) - [i50]Moses Charikar, Prasanna Ramakrishnan:
Metric Distortion Bounds for Randomized Social Choice. CoRR abs/2111.03694 (2021) - 2020
- [j31]Vladimir Braverman, Moses Charikar, William Kuszmaul, Lin F. Yang:
The one-way communication complexity of dynamic time warping distance. J. Comput. Geom. 11(2): 62-93 (2020) - [j30]Edward Gan, Peter Bailis, Moses Charikar:
CoopStore: Optimizing Precomputed Summaries for Aggregation. Proc. VLDB Endow. 13(11): 2174-2187 (2020) - [c118]Moses Charikar, Michael Kapralov, Navid Nouri, Paris Siminelakis:
Kernel Density Estimation through Density Constrained Near Neighbor Search. FOCS 2020: 172-183 - [c117]Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
Instance Based Approximations to Profile Maximum Likelihood. NeurIPS 2020 - [c116]Dan Garcia, Moses Charikar, Eboney Hearn, Ed Lazowska
, Jonathan Reynolds:
Institutions Share Successes, Failures, and Advice in Moving the Diversity Needle. SIGCSE 2020: 331-332 - [c115]Moses Charikar, Xian Wu, Yinyu Ye:
Adaptive Discrete Phase Retrieval. SOSA 2020: 47-56 - [c114]Moses Charikar, Weiyun Ma, Li-Yang Tan:
Unconditional Lower Bounds for Adaptive Massively Parallel Computation. SPAA 2020: 141-151 - [c113]Raunak Kumar, Paul Liu, Moses Charikar, Austin R. Benson:
Retrieving Top Weighted Triangles in Graphs. WSDM 2020: 295-303 - [i49]Moses Charikar, Weiyun Ma, Li-Yang Tan:
New lower bounds for Massively Parallel Computation from query complexity. CoRR abs/2001.01146 (2020) - [i48]Edward Gan, Peter Bailis, Moses Charikar:
Storyboard: Optimizing Precomputed Summaries for Aggregation. CoRR abs/2002.03063 (2020) - [i47]Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
A General Framework for Symmetric Property Estimation. CoRR abs/2003.00844 (2020) - [i46]Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood. CoRR abs/2004.02425 (2020) - [i45]Joshua Brakensiek, Moses Charikar, Aviad Rubinstein:
A Simple Sublinear Algorithm for Gap Edit Distance. CoRR abs/2007.14368 (2020) - [i44]Xian Wu, Moses Charikar:
Nearest Neighbor Search for Hyperbolic Embeddings. CoRR abs/2009.00836 (2020) - [i43]Moses Charikar, Paul Liu:
Improved Algorithms for Edge Colouring in the W-Streaming Model. CoRR abs/2010.14560 (2020) - [i42]Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
Instance Based Approximations to Profile Maximum Likelihood. CoRR abs/2011.02761 (2020) - [i41]Moses Charikar, Michael Kapralov, Navid Nouri, Paris Siminelakis:
Kernel Density Estimation through Density Constrained Near Neighbor Search. CoRR abs/2011.06997 (2020) - [i40]Moses Charikar, Shivam Garg, Deborah M. Gordon, Kirankumar Shiragur:
A Model for Ant Trail Formation and its Convergence Properties. CoRR abs/2011.14722 (2020)
2010 – 2019
- 2019
- [c112]Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh, Grigory Yaroslavtsev:
Hierarchical Clustering for Euclidean Data. AISTATS 2019: 2721-2730 - [c111]Hongyang Zhang, Vatsal Sharan, Moses Charikar, Yingyu Liang:
Recovery Guarantees For Quadratic Tensors With Sparse Observations. AISTATS 2019: 3322-3332 - [c110]Vladimir Braverman, Moses Charikar, William Kuszmaul, David P. Woodruff, Lin F. Yang:
The One-Way Communication Complexity of Dynamic Time Warping Distance. SoCG 2019: 16:1-16:15 - [c109]Moses Charikar, Paris Siminelakis:
Multi-resolution Hashing for Fast Pairwise Summations. FOCS 2019: 769-792 - [c108]Paris Siminelakis, Kexin Rong, Peter Bailis, Moses Charikar, Philip Alexander Levis:
Rehashing Kernel Evaluation in High Dimensions. ICML 2019: 5789-5798 - [c107]Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
A General Framework for Symmetric Property Estimation. NeurIPS 2019: 12426-12436 - [c106]Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh:
Hierarchical Clustering better than Average-Linkage. SODA 2019: 2291-2304 - [c105]Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
Efficient profile maximum likelihood for universal symmetric property estimation. STOC 2019: 780-791 - [c104]Paul Liu, Austin R. Benson, Moses Charikar:
Sampling Methods for Counting Temporal Motifs. WSDM 2019: 294-302 - [e3]Moses Charikar, Edith Cohen:
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, STOC 2019, Phoenix, AZ, USA, June 23-26, 2019. ACM 2019, ISBN 978-1-4503-6705-9 [contents] - [i39]Vladimir Braverman, Moses Charikar, William Kuszmaul, David P. Woodruff, Lin F. Yang:
The One-Way Communication Complexity of Dynamic Time Warping Distance. CoRR abs/1903.03520 (2019) - [i38]Moses Charikar, Kirankumar Shiragur, Aaron Sidford:
Efficient Profile Maximum Likelihood for Universal Symmetric Property Estimation. CoRR abs/1905.08448 (2019) - [i37]Raunak Kumar, Paul Liu, Moses Charikar, Austin R. Benson:
Retrieving Top Weighted Triangles in Graphs. CoRR abs/1910.00692 (2019) - 2018
- [c103]Moses Charikar, Yonatan Naamad, Jennifer Rexford, X. Kelvin Zou:
Multi-commodity Flow with In-Network Processing. ALGOCLOUD 2018: 73-101 - [c102]Arturs Backurs, Moses Charikar, Piotr Indyk, Paris Siminelakis:
Efficient Density Evaluation for Smooth Kernels. FOCS 2018: 615-626 - [c101]Moses Charikar, Shay Solomon:
Fully Dynamic Almost-Maximal Matching: Breaking the Polynomial Worst-Case Time Barrier. ICALP 2018: 33:1-33:14 - [c100]Moses Charikar, Ofir Geri, Michael P. Kim, William Kuszmaul:
On Estimating Edit Distance: Alignment, Dimension Reduction, and Embeddings. ICALP 2018: 34:1-34:14 - [c99]Vaggos Chatziafratis, Rad Niazadeh, Moses Charikar:
Hierarchical Clustering with Structural Constraints. ICML 2018: 773-782 - [c98]Xian Wu, Moses Charikar, Vishnu Natchu:
Local Density Estimation in High Dimensions. ICML 2018: 5293-5301 - [c97]Jacob Steinhardt, Moses Charikar, Gregory Valiant:
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers. ITCS 2018: 45:1-45:21 - [i36]Moses Charikar, Yonatan Naamad, Jimmy Wu:
On Finding Dense Common Subgraphs. CoRR abs/1802.06361 (2018) - [i35]Moses Charikar, Yonatan Naamad, Jennifer Rexford, X. Kelvin Zou:
Multi-Commodity Flow with In-Network Processing. CoRR abs/1802.09118 (2018) - [i34]Moses Charikar, Ofir Geri, Michael P. Kim, William Kuszmaul:
On Estimating Edit Distance: Alignment, Dimension Reduction, and Embeddings. CoRR abs/1804.09907 (2018) - [i33]Vaggos Chatziafratis, Rad Niazadeh, Moses Charikar:
Hierarchical Clustering with Structural Constraints. CoRR abs/1805.09476 (2018) - [i32]Moses Charikar, Paris Siminelakis:
Multi-Resolution Hashing for Fast Pairwise Summations. CoRR abs/1807.07635 (2018) - [i31]Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh:
Hierarchical Clustering better than Average-Linkage. CoRR abs/1808.02227 (2018) - [i30]Moses Charikar, Paris Siminelakis:
Hashing-Based-Estimators for Kernel Density in High Dimensions. CoRR abs/1808.10530 (2018) - [i29]Xian Wu, Moses Charikar, Vishnu Natchu:
Local Density Estimation in High Dimensions. CoRR abs/1809.07471 (2018) - [i28]Paul Liu, Austin R. Benson, Moses Charikar:
A sampling framework for counting temporal motifs. CoRR abs/1810.00980 (2018) - [i27]Hongyang Zhang, Vatsal Sharan, Moses Charikar, Yingyu Liang:
Recovery Guarantees for Quadratic Tensors with Limited Observations. CoRR abs/1811.00148 (2018) - [i26]Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh, Grigory Yaroslavtsev:
Hierarchical Clustering for Euclidean Data. CoRR abs/1812.10582 (2018) - 2017
- [j29]Qin Lv, William Josephson, Zhe Wang, Moses Charikar, Kai Li:
Intelligent Probing for Locality Sensitive Hashing: Multi-Probe LSH and Beyond. Proc. VLDB Endow. 10(12): 2021-2024 (2017) - [c96]Itai Ashlagi, Yossi Azar, Moses Charikar, Ashish Chiplunkar, Ofir Geri, Haim Kaplan, Rahul Makhijani, Yuyi Wang, Roger Wattenhofer:
Min-Cost Bipartite Perfect Matching with Delays. APPROX-RANDOM 2017: 1:1-1:20 - [c95]Yuchen Zhang, Percy Liang, Moses Charikar:
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics. COLT 2017: 1980-2022 - [c94]Moses Charikar, Paris Siminelakis:
Hashing-Based-Estimators for Kernel Density in High Dimensions. FOCS 2017: 1032-1043 - [c93]Moses Charikar, Neha Gupta, Roy Schwartz:
Local Guarantees in Graph Cuts and Clustering. IPCO 2017: 136-147 - [c92]Moses Charikar, Vaggos Chatziafratis:
Approximate Hierarchical Clustering via Sparsest Cut and Spreading Metrics. SODA 2017: 841-854 - [c91]Moses Charikar, Jacob Steinhardt, Gregory Valiant:
Learning from untrusted data. STOC 2017: 47-60 - [i25]Yuchen Zhang, Percy Liang, Moses Charikar:
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics. CoRR abs/1702.05575 (2017) - [i24]Jacob Steinhardt, Moses Charikar, Gregory Valiant:
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers. CoRR abs/1703.04940 (2017) - [i23]Moses Charikar, Neha Gupta, Roy Schwartz:
Local Guarantees in Graph Cuts and Clustering. CoRR abs/1704.00355 (2017) - [i22]Moses Charikar, Shay Solomon:
Fully Dynamic Almost-Maximal Matching: Breaking the Polynomial Barrier for Worst-Case Time Bounds. CoRR abs/1711.06883 (2017) - 2016
- [c90]Moses Charikar, Yonatan Naamad, Anthony Wirth:
On Approximating Target Set Selection. APPROX-RANDOM 2016: 4:1-4:16 - [c89]Pranjal Awasthi, Moses Charikar, Ravishankar Krishnaswamy, Ali Kemal Sinop:
Spectral Embedding of k-Cliques, Graph Partitioning and k-Means. ITCS 2016: 301-310 - [c88]Jacob Steinhardt, Gregory Valiant, Moses Charikar:
Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction. NIPS 2016: 4439-4447 - [p1]Moses Charikar:
Top-k Frequent Item Maintenance over Streams. Data Stream Management 2016: 103-119 - [i21]Jacob Steinhardt, Gregory Valiant, Moses Charikar:
Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction. CoRR abs/1606.05374 (2016) - [i20]Moses Charikar, Vaggos Chatziafratis:
Approximate Hierarchical Clustering via Sparsest Cut and Spreading Metrics. CoRR abs/1609.09548 (2016) - [i19]Moses Charikar, Jacob Steinhardt, Gregory Valiant:
Learning from Untrusted Data. CoRR abs/1611.02315 (2016) - 2015
- [c87]Pranjal Awasthi, Moses Charikar, Kevin A. Lai, Andrej Risteski:
Label optimal regret bounds for online local learning. COLT 2015: 150-166 - [c86]Pranjal Awasthi, Moses Charikar, Ravishankar Krishnaswamy, Ali Kemal Sinop:
The Hardness of Approximation of Euclidean k-Means. SoCG 2015: 754-767 - [c85]Moses Samson Charikar:
Bypassing Worst Case Analysis: Tensor Decomposition and Clustering (Invited Talk). FSTTCS 2015: 1 - [c84]Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel Ward:
Relax, No Need to Round: Integrality of Clustering Formulations. ITCS 2015: 191-200 - [i18]Pranjal Awasthi, Moses Charikar, Ravishankar Krishnaswamy, Ali Kemal Sinop:
The Hardness of Approximation of Euclidean k-means. CoRR abs/1502.03316 (2015) - [i17]Pranjal Awasthi, Moses Charikar, Kevin A. Lai, Andrej Risteski:
Label optimal regret bounds for online local learning. CoRR abs/1503.02193 (2015) - 2014
- [c83]Aditya Bhaskara, Moses Charikar, Aravindan Vijayaraghavan:
Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability. COLT 2014: 742-778 - [c82]Aditya Bhaskara, Moses Charikar, Ankur Moitra, Aravindan Vijayaraghavan:
Open Problem: Tensor Decompositions: Algorithms up to the Uniqueness Threshold? COLT 2014: 1280-1282 - [c81]Moses Charikar, Monika Henzinger, Huy L. Nguyen:
Online Bipartite Matching with Decomposable Weights. ESA 2014: 260-271 - [c80]Afonso S. Bandeira, Moses Charikar, Amit Singer, Andy Zhu:
Multireference alignment using semidefinite programming. ITCS 2014: 459-470 - [c79]Nikhil Bansal, Moses Charikar, Ravishankar Krishnaswamy, Shi Li:
Better Algorithms and Hardness for Broadcast Scheduling via a Discrepancy Approach. SODA 2014: 55-71 - [c78]Aditya Bhaskara, Moses Charikar, Ankur Moitra, Aravindan Vijayaraghavan:
Smoothed analysis of tensor decompositions. STOC 2014: 594-603 - [i16]Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel Ward:
Relax, no need to round: integrality of clustering formulations. CoRR abs/1408.4045 (2014) - [i15]Moses Charikar, Monika Henzinger, Huy L. Nguyen:
Online Bipartite Matching with Decomposable Weights. CoRR abs/1409.2139 (2014) - 2013
- [i14]Aditya Bhaskara, Moses Charikar, Aravindan Vijayaraghavan:
Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability. CoRR abs/1304.8087 (2013) - [i13]Afonso S. Bandeira, Moses Charikar, Amit Singer, Andy Zhu:
Multireference Alignment using Semidefinite Programming. CoRR abs/1308.5256 (2013) - [i12]Aditya Bhaskara, Moses Charikar, Ankur Moitra, Aravindan Vijayaraghavan:
Smoothed Analysis of Tensor Decompositions. CoRR abs/1311.3651 (2013) - 2012
- [c77]Aditya Bhaskara, Moses Charikar, Rajsekar Manokaran, Aravindan Vijayaraghavan:
On Quadratic Programming with a Ratio Objective. ICALP (1) 2012: 109-120 - [c76]Moses Charikar, Shi Li:
A Dependent LP-Rounding Approach for the k-Median Problem. ICALP (1) 2012: 194-205 - [c75]Wei Dong, Zhe Wang, Moses Charikar, Kai Li:
High-confidence near-duplicate image detection. ICMR 2012: 1 - [c74]Aditya Bhaskara, Moses Charikar, Aravindan Vijayaraghavan, Venkatesan Guruswami, Yuan Zhou:
Polynomial integrality gaps for strong SDP relaxations of Densest k-subgraph. SODA 2012: 388-405 - 2011
- [j28]Moses Charikar, MohammadTaghi Hajiaghayi, Howard J. Karloff:
Improved Approximation Algorithms for Label Cover Problems. Algorithmica 61(1): 190-206 (2011) - [j27]Venkatesan Guruswami, Johan Håstad, Rajsekar Manokaran, Prasad Raghavendra, Moses Charikar:
Beating the Random Ordering Is Hard: Every Ordering CSP Is Approximation Resistant. SIAM J. Comput. 40(3): 878-914 (2011) - [j26]Nir Ailon, Moses Charikar:
Fitting Tree Metrics: Hierarchical Clustering and Phylogeny. SIAM J. Comput. 40(5): 1275-1291 (2011) - [c73]Alexandr Andoni, Moses Charikar, Ofer Neiman, Huy L. Nguyen:
Near Linear Lower Bound for Dimension Reduction in L1. FOCS 2011: 315-323 - [c72]Moses Charikar, Alantha Newman, Aleksandar Nikolov:
Tight Hardness Results for Minimizing Discrepancy. SODA 2011: 1607-1614 - [c71]Wei Dong, Moses Charikar, Kai Li:
Efficient k-nearest neighbor graph construction for generic similarity measures. WWW 2011: 577-586 - [i11]Aditya Bhaskara, Moses Charikar, Rajsekar Manokaran, Aravindan Vijayaraghavan:
On Quadratic Programming with a Ratio Objective. CoRR abs/1101.1710 (2011) - [i10]Aditya Bhaskara, Moses Charikar, Venkatesan Guruswami, Aravindan Vijayaraghavan, Yuan Zhou:
Polynomial integrality gaps for strong SDP relaxations of Densest k-subgraph. CoRR abs/1110.1360 (2011) - [i9]Venkatesan Guruswami, Johan Håstad, Rajsekar Manokaran, Prasad Raghavendra, Moses Charikar:
Beating the Random Ordering is Hard: Every ordering CSP is approximation resistant. Electron. Colloquium Comput. Complex. TR11 (2011) - 2010
- [j25]Moses Charikar, Mohammad Taghi Hajiaghayi, Howard J. Karloff, Satish Rao:
l22 Spreading Metrics for Vertex Ordering Problems. Algorithmica 56(4): 577-604 (2010) - [j24]Moses Charikar, Konstantin Makarychev, Yury Makarychev:
Local Global Tradeoffs in Metric Embeddings. SIAM J. Comput. 39(6): 2487-2512 (2010) - [c70]Moses Charikar, Tom Leighton, Shi Li, Ankur Moitra:
Vertex Sparsifiers and Abstract Rounding Algorithms. FOCS 2010: 265-274 - [c69]Aditya Bhaskara, Moses Charikar, Eden Chlamtac, Uriel Feige, Aravindan Vijayaraghavan:
Detecting high log-densities: an O(n1/4) approximation for densest k-subgraph. STOC 2010: 201-210 - [e2]Moses Charikar:
Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2010, Austin, Texas, USA, January 17-19, 2010. SIAM 2010, ISBN 978-0-89871-701-3 [contents] - [i8]Aditya Bhaskara, Moses Charikar, Eden Chlamtac, Uriel Feige, Aravindan Vijayaraghavan:
Detecting High Log-Densities -- an O(n^1/4) Approximation for Densest k-Subgraph. CoRR abs/1001.2891 (2010) - [i7]Prahladh Harsha, Moses Charikar, Matthew Andrews, Sanjeev Arora, Subhash Khot, Dana Moshkovitz, Lisa Zhang, Ashkan Aazami, Dev Desai, Igor Gorodezky, Geetha Jagannathan, Alexander S. Kulikov, Darakhshan J. Mir, Alantha Newman, Aleksandar Nikolov, David Pritchard, Gwen Spencer:
Limits of Approximation Algorithms: PCPs and Unique Games (DIMACS Tutorial Lecture Notes). CoRR abs/1002.3864 (2010) - [i6]Moses Charikar, Tom Leighton, Shi Li, Ankur Moitra:
Vertex Sparsifiers and Abstract Rounding Algorithms. CoRR abs/1006.4536 (2010)
2000 – 2009
- 2009
- [j23]