Moses Charikar

ORCID

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 107

Top Venues

Publications

Moses Charikar, Kangning Wang, Prasanna Ramakrishnan, Hongxun Wu
Breaking the Metric Voting Distortion Barrier. SODA (2024)
Moses Charikar, Michael Kapralov, Erik Waingarten
A Quasi-Monte Carlo Data Structure for Smooth Kernel Evaluations. CoRR (2024)
Moses Charikar, Michael Kapralov, Erik Waingarten
A Quasi-Monte Carlo Data Structure for Smooth Kernel Evaluations. SODA (2024)
Soheil Behnezhad, Moses Charikar, Vincent Cohen-Addad, Alma Ghafari, Weiyun Ma
Fully Dynamic Correlation Clustering: Breaking 3-Approximation. CoRR (2024)
Moses Charikar, Ruiquan Gao
Improved Approximations for Ultrametric Violation Distance. SODA (2024)
Kexin Rong, Paul Liu, Sarah Ashok Sonje, Moses Charikar
Dynamic Data Layout Optimization with Worst-Case Guarantees. ICDE (2024)
Kexin Rong, Paul Liu, Sarah Ashok Sonje, Moses Charikar
Dynamic Data Layout Optimization with Worst-case Guarantees. CoRR (2024)
Moses Charikar, Chirag Pabbaraju, Kirankumar Shiragur
Quantifying the Gain in Weak-to-Strong Generalization. CoRR (2024)
Moses Charikar, Chirag Pabbaraju
A Characterization of List Learnability. STOC (2023)
Moses Charikar, Beidi Chen, Christopher Ré, Erik Waingarten
Fast Algorithms for a New Relaxation of Optimal Transport. CoRR (2023)
Nima Anari, Moses Charikar, Prasanna Ramakrishnan
Distortion in metric matching with ordinal preferences. EC (2023)
Soheil Behnezhad, Moses Charikar, Weiyun Ma, Li-Yang Tan
Single-Pass Streaming Algorithms for Correlation Clustering. SODA (2023)
Moses Charikar, Spencer Compton, Chirag Pabbaraju
: Tree Ising Models. CoRR (2023)
Moses Charikar, Ruiquan Gao
Improved Approximations for Ultrametric Violation Distance. CoRR (2023)
Moses Charikar, Prasanna Ramakrishnan, Kangning Wang, Hongxun Wu
Breaking the Metric Voting Distortion Barrier. CoRR (2023)
Moses Charikar, Beidi Chen, Christopher Ré, Erik Waingarten
Fast Algorithms for a New Relaxation of Optimal Transport. COLT (2023)
Moses Charikar, Monika Henzinger, Lunjia Hu, Maximilian Vötsch, Erik Waingarten
Simple, Scalable and Effective Clustering via One-Dimensional Projections. NeurIPS (2023)
Moses Charikar, Monika Henzinger, Lunjia Hu, Maximilian Vötsch, Erik Waingarten
Simple, Scalable and Effective Clustering via One-Dimensional Projections. CoRR (2023)
Nima Anari, Moses Charikar, Prasanna Ramakrishnan
Distortion in metric matching with ordinal preferences. CoRR (2023)
Moses Charikar, Lunjia Hu
Near-Optimal Explainable k-Means for All Dimensions. SODA (2022)
Moses Charikar, Chirag Pabbaraju
A Characterization of List Learnability. CoRR (2022)
Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. NeurIPS (2022)
Moses Charikar, Erik Waingarten
The Johnson-Lindenstrauss Lemma for Clustering and Subspace Approximation: From Coresets to Dimension Reduction. CoRR (2022)
Moses Charikar, Erik Waingarten
Polylogarithmic Sketches for Clustering. CoRR (2022)
Xian Wu, Moses Charikar, Vishnu Natchu
Local Density Estimation in High Dimensions. Math. Oper. Res. 47 (4) (2022)
Soheil Behnezhad, Moses Charikar, Weiyun Ma, Li-Yang Tan
Almost 3-Approximate Correlation Clustering in Constant Rounds. FOCS (2022)
Moses Charikar, Prasanna Ramakrishnan
Metric Distortion Bounds for Randomized Social Choice. SODA (2022)
Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. CoRR (2022)
Moses Charikar, Erik Waingarten
Polylogarithmic Sketches for Clustering. ICALP (2022)
Soheil Behnezhad, Moses Charikar, Weiyun Ma, Li-Yang Tan
Almost 3-Approximate Correlation Clustering in Constant Rounds. CoRR (2022)
Moses Charikar, Paul Liu, Tianyu Liu, Thuy-Duong Vuong
On the Complexity of Sampling Redistricting Plans. CoRR (2022)
Guy Blanc, Moses Charikar
Multiway Online Correlated Selection. FOCS (2022)
Guy Blanc, Moses Charikar
Multiway Online Correlated Selection. FOCS (2021)
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)
Moses Charikar, Lunjia Hu
Approximation Algorithms for Orthogonal Non-negative Matrix Factorization. AISTATS (2021)
Moses Charikar, Paul Liu
Improved Algorithms for Edge Colouring in the W-Streaming Model. SOSA (2021)
Moses Charikar, Shivam Garg, Deborah M. Gordon, Kirankumar Shiragur
A Model for Ant Trail Formation and its Convergence Properties (Extended Abstract). ITCS (2021)
Moses Charikar, Lunjia Hu
Near-Optimal Explainable k-Means for All Dimensions. CoRR (2021)
Moses Charikar, Weiyun Ma, Li-Yang Tan
Brief Announcement: A Randomness-efficient Massively Parallel Algorithm for Connectivity. PODC (2021)
Moses Charikar, Lunjia Hu
Approximation Algorithms for Orthogonal Non-negative Matrix Factorization. CoRR (2021)
Moses Charikar, Prasanna Ramakrishnan
Metric Distortion Bounds for Randomized Social Choice. CoRR (2021)
Guy Blanc, Moses Charikar
Multiway Online Correlated Selection. CoRR (2021)
Dan Garcia, Moses Charikar, Eboney Hearn, Ed Lazowska, Jonathan Reynolds
Institutions Share Successes, Failures, and Advice in Moving the Diversity Needle. SIGCSE (2020)
Joshua Brakensiek, Moses Charikar, Aviad Rubinstein
A Simple Sublinear Algorithm for Gap Edit Distance. CoRR (2020)
Vladimir Braverman, Moses Charikar, William Kuszmaul, Lin F. Yang
The one-way communication complexity of dynamic time warping distance. J. Comput. Geom. 11 (2) (2020)
Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford
Instance Based Approximations to Profile Maximum Likelihood. NeurIPS (2020)
Moses Charikar, Xian Wu, Yinyu Ye
Adaptive Discrete Phase Retrieval. SOSA (2020)
Edward Gan, Peter Bailis, Moses Charikar
Storyboard: Optimizing Precomputed Summaries for Aggregation. CoRR (2020)
Moses Charikar, Michael Kapralov, Navid Nouri, Paris Siminelakis
Kernel Density Estimation through Density Constrained Near Neighbor Search. CoRR (2020)
Edward Gan, Peter Bailis, Moses Charikar
CoopStore: Optimizing Precomputed Summaries for Aggregation. Proc. VLDB Endow. 13 (11) (2020)
Raunak Kumar, Paul Liu, Moses Charikar, Austin R. Benson
Retrieving Top Weighted Triangles in Graphs. WSDM (2020)
Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford
The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood. CoRR (2020)
Moses Charikar, Kirankumar Shiragur, Aaron Sidford
A General Framework for Symmetric Property Estimation. CoRR (2020)
Xian Wu, Moses Charikar
Nearest Neighbor Search for Hyperbolic Embeddings. CoRR (2020)
Moses Charikar, Weiyun Ma, Li-Yang Tan
New lower bounds for Massively Parallel Computation from query complexity. CoRR (2020)
Moses Charikar, Paul Liu
Improved Algorithms for Edge Colouring in the W-Streaming Model. CoRR (2020)
Moses Charikar, Shivam Garg, Deborah M. Gordon, Kirankumar Shiragur
A Model for Ant Trail Formation and its Convergence Properties. CoRR (2020)
Moses Charikar, Weiyun Ma, Li-Yang Tan
Unconditional Lower Bounds for Adaptive Massively Parallel Computation. SPAA (2020)
Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford
Instance Based Approximations to Profile Maximum Likelihood. CoRR (2020)
Moses Charikar, Michael Kapralov, Navid Nouri, Paris Siminelakis
Kernel Density Estimation through Density Constrained Near Neighbor Search. FOCS (2020)
Moses Charikar, Kirankumar Shiragur, Aaron Sidford
Efficient Profile Maximum Likelihood for Universal Symmetric Property Estimation. CoRR (2019)
Paul Liu, Austin R. Benson, Moses Charikar
Sampling Methods for Counting Temporal Motifs. WSDM (2019)
Moses Charikar, Kirankumar Shiragur, Aaron Sidford
A General Framework for Symmetric Property Estimation. NeurIPS (2019)
Vladimir Braverman, Moses Charikar, William Kuszmaul, David P. Woodruff, Lin F. Yang
The One-Way Communication Complexity of Dynamic Time Warping Distance. SoCG (2019)
Moses Charikar, Kirankumar Shiragur, Aaron Sidford
Efficient profile maximum likelihood for universal symmetric property estimation. STOC (2019)
Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh
Hierarchical Clustering better than Average-Linkage. SODA (2019)
Paris Siminelakis, Kexin Rong, Peter Bailis, Moses Charikar, Philip Alexander Levis
Rehashing Kernel Evaluation in High Dimensions. ICML (2019)
Vladimir Braverman, Moses Charikar, William Kuszmaul, David P. Woodruff, Lin F. Yang
The One-Way Communication Complexity of Dynamic Time Warping Distance. CoRR (2019)
Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh, Grigory Yaroslavtsev
Hierarchical Clustering for Euclidean Data. AISTATS (2019)
Raunak Kumar, Paul Liu, Moses Charikar, Austin R. Benson
Retrieving Top Weighted Triangles in Graphs. CoRR (2019)
Moses Charikar, Paris Siminelakis
Multi-resolution Hashing for Fast Pairwise Summations. FOCS (2019)
Hongyang Zhang, Vatsal Sharan, Moses Charikar, Yingyu Liang
Recovery Guarantees For Quadratic Tensors With Sparse Observations. AISTATS (2019)
Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh
Hierarchical Clustering better than Average-Linkage. CoRR (2018)
Moses Charikar, Paris Siminelakis
Multi-Resolution Hashing for Fast Pairwise Summations. CoRR (2018)
Paul Liu, Austin R. Benson, Moses Charikar
A sampling framework for counting temporal motifs. CoRR (2018)
Moses Charikar, Yonatan Naamad, Jennifer Rexford, X. Kelvin Zou
Multi-commodity Flow with In-Network Processing. ALGOCLOUD (2018)
Moses Charikar, Yonatan Naamad, Jennifer Rexford, X. Kelvin Zou
Multi-Commodity Flow with In-Network Processing. CoRR (2018)
Xian Wu, Moses Charikar, Vishnu Natchu
Local Density Estimation in High Dimensions. CoRR (2018)
Moses Charikar, Ofir Geri, Michael P. Kim, William Kuszmaul
On Estimating Edit Distance: Alignment, Dimension Reduction, and Embeddings. CoRR (2018)
Moses Charikar, Yonatan Naamad, Jimmy Wu
On Finding Dense Common Subgraphs. CoRR (2018)
Arturs Backurs, Moses Charikar, Piotr Indyk, Paris Siminelakis
Efficient Density Evaluation for Smooth Kernels. FOCS (2018)
Vaggos Chatziafratis, Rad Niazadeh, Moses Charikar
Hierarchical Clustering with Structural Constraints. ICML (2018)
Moses Charikar, Ofir Geri, Michael P. Kim, William Kuszmaul
On Estimating Edit Distance: Alignment, Dimension Reduction, and Embeddings. ICALP (2018)
Hongyang Zhang, Vatsal Sharan, Moses Charikar, Yingyu Liang
Recovery Guarantees for Quadratic Tensors with Limited Observations. CoRR (2018)
Moses Charikar, Paris Siminelakis
Hashing-Based-Estimators for Kernel Density in High Dimensions. CoRR (2018)
Xian Wu, Moses Charikar, Vishnu Natchu
Local Density Estimation in High Dimensions. ICML (2018)
Moses Charikar, Shay Solomon
Fully Dynamic Almost-Maximal Matching: Breaking the Polynomial Worst-Case Time Barrier. ICALP (2018)
Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh, Grigory Yaroslavtsev
Hierarchical Clustering for Euclidean Data. CoRR (2018)
Jacob Steinhardt, Moses Charikar, Gregory Valiant
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers. ITCS (2018)
Vaggos Chatziafratis, Rad Niazadeh, Moses Charikar
Hierarchical Clustering with Structural Constraints. CoRR (2018)
Moses Charikar, Neha Gupta, Roy Schwartz
Local Guarantees in Graph Cuts and Clustering. CoRR (2017)
Yuchen Zhang, Percy Liang, Moses Charikar
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics. CoRR (2017)
Jacob Steinhardt, Moses Charikar, Gregory Valiant
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers. CoRR (2017)
Moses Charikar, Shay Solomon
Fully Dynamic Almost-Maximal Matching: Breaking the Polynomial Barrier for Worst-Case Time Bounds. CoRR (2017)
Moses Charikar, Paris Siminelakis
Hashing-Based-Estimators for Kernel Density in High Dimensions. FOCS (2017)
Moses Charikar, Vaggos Chatziafratis
Approximate Hierarchical Clustering via Sparsest Cut and Spreading Metrics. SODA (2017)
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) (2017)
Moses Charikar, Neha Gupta, Roy Schwartz
Local Guarantees in Graph Cuts and Clustering. IPCO (2017)
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)
Moses Charikar, Jacob Steinhardt, Gregory Valiant
Learning from untrusted data. STOC (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Moses Charikar