Michael Kapralov

134 papers A* 54A 9Journal 65Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	Recovering Communities in Structured Random Graphs. ITCS Michael Kapralov, Luca Trevisan, Weronika Wrzos-Kaminska
2026	J	`jnl`	Recovering Communities in Structured Random Graphs. CoRR Michael Kapralov, Luca Trevisan, Weronika Wrzos-Kaminska
2026	J	`jnl`	Spectral Clustering in Birthday Paradox Time. CoRR Michael Kapralov, Ekaterina Kochetkova, Weronika Wrzos-Kaminska
2026	A*	`conf`	Spectral Clustering with Side Information. SODA Hendrik Fichtenberger, Michael Kapralov, Ekaterina Kochetkova, Silvio Lattanzi, Davide Mazzali, Weronika Wrzos-Kaminska
2026	A*	`conf`	Spectral clustering in birthday paradox time. SODA Michael Kapralov, Ekaterina Kochetkova, Weronika Wrzos-Kaminska
2026	A*	`conf`	Sublinear Time Low-Rank Approximation of Hankel Matrices. SODA Michael Kapralov, Cameron Musco, Kshiteej Sheth
2025	A*	`conf`	Approximating Dasgupta Cost in Sublinear Time from a Few Random Seeds. ICALP Michael Kapralov, Akash Kumar, Silvio Lattanzi, Aida Mousavifar, Weronika Wrzos-Kaminska
2025	J	`jnl`	BalanceKV: KV Cache Compression through Discrepancy Theory. CoRR Insu Han, Michael Kapralov, Ekaterina Kochetkova, Kshiteej Sheth, Amir Zandieh
2025	A*	`conf`	Generalized Flow in Nearly-linear Time on Moderately Dense Graphs. FOCS Shunhua Jiang, Michael Kapralov, Lawrence Li, Aaron Sidford
2025	J	`jnl`	Generalized Flow in Nearly-linear Time on Moderately Dense Graphs. CoRR Shunhua Jiang, Michael Kapralov, Lawrence Li, Aaron Sidford
2025	A*	`conf`	Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions. ICLR Piotr Indyk, Michael Kapralov, Kshiteej Sheth, Tal Wagner
2025	J	`jnl`	Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions. CoRR Piotr Indyk, Michael Kapralov, Kshiteej Sheth, Tal Wagner
2025	J	`jnl`	On the Adversarial Robustness of Locality-Sensitive Hashing in Hamming Space. Proc. ACM Manag. Data Michael Kapralov, Mikhail Makarov, Christian Sohler
2025	J	`jnl`	Spectral Clustering with Side Information. CoRR Hendrik Fichtenberger, Michael Kapralov, Ekaterina Kochetkova, Silvio Lattanzi, Davide Mazzali, Weronika Wrzos-Kaminska
2025	J	`jnl`	Sublinear Time Low-Rank Approximation of Hankel Matrices. CoRR Michael Kapralov, Cameron Musco, Kshiteej Sheth
2024	A*	`conf`	A Quasi-Monte Carlo Data Structure for Smooth Kernel Evaluations. SODA Moses Charikar, Michael Kapralov, Erik Waingarten
2024	J	`jnl`	A Quasi-Monte Carlo Data Structure for Smooth Kernel Evaluations. CoRR Moses Charikar, Michael Kapralov, Erik Waingarten
2024	A*	`conf`	On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models. NeurIPS Aditya Bhaskara, Agastya Vibhuti Jha, Michael Kapralov, Naren Manoj, Davide Mazzali, Weronika Wrzos-Kaminska
2024	J	`jnl`	On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models. CoRR Aditya Bhaskara, Agastya Vibhuti Jha, Michael Kapralov, Naren Sarayu Manoj, Davide Mazzali, Weronika Wrzos-Kaminska
2024	A*	`conf`	On the Streaming Complexity of Expander Decomposition. ICALP Yu Chen, Michael Kapralov, Mikhail Makarov, Davide Mazzali
2024	J	`jnl`	On the Streaming Complexity of Expander Decomposition. CoRR Yu Chen, Michael Kapralov, Mikhail Makarov, Davide Mazzali
2024	J	`jnl`	On the adversarial robustness of Locality-Sensitive Hashing in Hamming space. CoRR Michael Kapralov, Mikhail Makarov, Christian Sohler
2024	A*	`conf`	Streaming Algorithms for Connectivity Augmentation. ICALP Ce Jin, Michael Kapralov, Sepideh Mahabadi, Ali Vakilian
2024	J	`jnl`	Streaming Algorithms for Connectivity Augmentation. CoRR Ce Jin, Michael Kapralov, Sepideh Mahabadi, Ali Vakilian
2023	A	`conf`	Expander Decomposition in Dynamic Streams. ITCS Arnold Filtser, Michael Kapralov, Mikhail Makarov
2023	A*	`conf`	Learning Hierarchical Cluster Structure of Graphs in Sublinear Time. SODA Michael Kapralov, Akash Kumar, Silvio Lattanzi, Aida Mousavifar
2023	A	`conf`	On Constructing Spanners from Random Gaussian Projections. APPROX/RANDOM Sepehr Assadi, Michael Kapralov, Huacheng Yu
2023	J	`jnl`	Practice of Streaming Processing of Dynamic Graphs: Concepts, Models, and Systems. IEEE Trans. Parallel Distributed Syst. Maciej Besta, Marc Fischer, Vasiliki Kalavri, Michael Kapralov, Torsten Hoefler
2023	A*	`conf`	Toeplitz Low-Rank Approximation with Sublinear Query Complexity. SODA Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth
2023	A*	`conf`	Traversing the FFT Computation Tree for Dimension-Independent Sparse Fourier Transforms. SODA Karl Bringmann, Michael Kapralov, Mikhail Makarov, Vasileios Nakos, Amir Yagudin, Amir Zandieh
2022	J	`jnl`	Expander Decomposition in Dynamic Streams. CoRR Arnold Filtser, Michael Kapralov, Mikhail Makarov
2022	A*	`conf`	Factorial Lower Bounds for (Almost) Random Order Streams. FOCS Ashish Chiplunkar, John Kallaugher, Michael Kapralov, Eric Price
2022	J	`jnl`	Learning Hierarchical Structure of Clusterable Graphs. CoRR Michael Kapralov, Akash Kumar, Silvio Lattanzi, Aida Mousavifar
2022	A*	`conf`	Motif Cut Sparsifiers. FOCS Michael Kapralov, Mikhail Makarov, Sandeep Silwal, Christian Sohler, Jakab Tardos
2022	J	`jnl`	Motif Cut Sparsifiers. CoRR Michael Kapralov, Mikhail Makarov, Sandeep Silwal, Christian Sohler, Jakab Tardos
2022	A	`conf`	Noisy Boolean Hidden Matching with Applications. ITCS Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou
2022	J	`jnl`	On Constructing Spanners from Random Gaussian Projections. CoRR Sepehr Assadi, Michael Kapralov, Huacheng Yu
2022	A*	`conf`	Simulating Random Walks in Random Streams. SODA John Kallaugher, Michael Kapralov, Eric Price
2022	J	`jnl`	Toeplitz Low-Rank Approximation with Sublinear Query Complexity. CoRR Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth
2021	J	`jnl`	Approximating Local Graph Structure in Almost Random Order Streams. CoRR Ashish Chiplunkar, John Kallaugher, Michael Kapralov, Eric Price
2021	—	`conf`	Communication Efficient Coresets for Maximum Matching. SOSA Michael Kapralov, Gilbert Maystre, Jakab Tardos
2021	A*	`conf`	Efficient and Local Parallel Random Walks. NeurIPS Michael Kapralov, Silvio Lattanzi, Navid Nouri, Jakab Tardos
2021	J	`jnl`	Efficient and Local Parallel Random Walks. CoRR Michael Kapralov, Silvio Lattanzi, Navid Nouri, Jakab Tardos
2021	A*	`conf`	Graph Spanners by Sketching in Dynamic Streams and the Simultaneous Communication Model. SODA Arnold Filtser, Michael Kapralov, Navid Nouri
2021	J	`jnl`	Noisy Boolean Hidden Matching with Applications. CoRR Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou
2021	J	`jnl`	Simulating Random Walks in Random Streams. CoRR John Kallaugher, Michael Kapralov, Eric Price
2021	A*	`conf`	Space Lower Bounds for Approximating Maximum Matching in the Edge Arrival Model. SODA Michael Kapralov
2021	J	`jnl`	Space Lower Bounds for Approximating Maximum Matching in the Edge Arrival Model. CoRR Michael Kapralov
2021	J	`jnl`	Sparse Fourier Transform by traversing Cooley-Tukey FFT computation graphs. CoRR Karl Bringmann, Michael Kapralov, Mikhail Makarov, Vasileios Nakos, Amir Yagudin, Amir Zandieh
2021	A*	`conf`	Spectral Clustering Oracles in Sublinear Time. SODA Grzegorz Gluch, Michael Kapralov, Silvio Lattanzi, Aida Mousavifar, Christian Sohler
2021	J	`jnl`	Spectral Clustering Oracles in Sublinear Time. CoRR Grzegorz Gluch, Michael Kapralov, Silvio Lattanzi, Aida Mousavifar, Christian Sohler
2021	A*	`conf`	Spectral Hypergraph Sparsifiers of Nearly Linear Size. FOCS Michael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi Yoshida
2021	J	`jnl`	Spectral Hypergraph Sparsifiers of Nearly Linear Size. CoRR Michael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi Yoshida
2021	A*	`conf`	Towards tight bounds for spectral sparsification of hypergraphs. STOC Michael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi Yoshida
2020	J	`jnl`	Communication Efficient Coresets for Maximum Matching. CoRR Michael Kapralov, Gilbert Maystre, Jakab Tardos
2020	A*	`conf`	Differentially Private Release of Synthetic Graphs. SODA Marek Eliás, Michael Kapralov, Janardhan Kulkarni, Yin Tat Lee
2020	A*	`conf`	Fast and Space Efficient Spectral Sparsification in Dynamic Streams. SODA Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri, Aaron Sidford, Jakab Tardos
2020	J	`jnl`	Graph Spanners by Sketching in Dynamic Streams and the Simultaneous Communication Model. CoRR Arnold Filtser, Michael Kapralov, Navid Nouri
2020	A*	`conf`	Kernel Density Estimation through Density Constrained Near Neighbor Search. FOCS Moses Charikar, Michael Kapralov, Navid Nouri, Paris Siminelakis
2020	J	`jnl`	Kernel Density Estimation through Density Constrained Near Neighbor Search. CoRR Moses Charikar, Michael Kapralov, Navid Nouri, Paris Siminelakis
2020	A*	`conf`	Oblivious Sketching of High-Degree Polynomial Kernels. SODA Thomas D. Ahle, Michael Kapralov, Jakob Bæk Tejs Knudsen, Rasmus Pagh, Ameya Velingker, David P. Woodruff, Amir Zandieh
2020	A	`conf`	Scaling up Kernel Ridge Regression via Locality Sensitive Hashing. AISTATS Amir Zandieh, Navid Nouri, Ameya Velingker, Michael Kapralov, Ilya P. Razenshteyn
2020	J	`jnl`	Scaling up Kernel Ridge Regression via Locality Sensitive Hashing. CoRR Michael Kapralov, Navid Nouri, Ilya P. Razenshteyn, Ameya Velingker, Amir Zandieh
2020	A*	`conf`	Space Efficient Approximation to Maximum Matching Size from Uniform Edge Samples. SODA Michael Kapralov, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakab Tardos
2020	J	`jnl`	Towards Tight Bounds for Spectral Sparsification of Hypergraphs. CoRR Michael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi Yoshida
2019	A	`conf`	A Simple Sublinear-Time Algorithm for Counting Arbitrary Subgraphs via Edge Sampling. ITCS Sepehr Assadi, Michael Kapralov, Sanjeev Khanna
2019	A*	`conf`	A universal sampling method for reconstructing signals with simple Fourier transforms. STOC Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2019	A*	`conf`	An optimal space lower bound for approximating MAX-CUT. STOC Michael Kapralov, Dmitry Krachun
2019	A*	`conf`	Dimension-independent Sparse Fourier Transform. SODA Michael Kapralov, Ameya Velingker, Amir Zandieh
2019	J	`jnl`	Dimension-independent Sparse Fourier Transform. CoRR Michael Kapralov, Ameya Velingker, Amir Zandieh
2019	J	`jnl`	Dynamic Streaming Spectral Sparsification in Nearly Linear Time and Space. CoRR Michael Kapralov, Navid Nouri, Aaron Sidford, Jakab Tardos
2019	A*	`conf`	Efficiently Learning Fourier Sparse Set Functions. NeurIPS Andisheh Amrollahi, Amir Zandieh, Michael Kapralov, Andreas Krause
2019	J	`jnl`	Faster Spectral Sparsification in Dynamic Streams. CoRR Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri
2019	J	`jnl`	Oblivious Sketching of High-Degree Polynomial Kernels. CoRR Thomas D. Ahle, Michael Kapralov, Jakob Bæk Tejs Knudsen, Rasmus Pagh, Ameya Velingker, David P. Woodruff, Amir Zandieh
2019	A*	`conf`	Online Matching with General Arrivals. FOCS Buddhima Gamlath, Michael Kapralov, Andreas Maggiori, Ola Svensson, David Wajc
2019	J	`jnl`	Online Matching with General Arrivals. CoRR Buddhima Gamlath, Michael Kapralov, Andreas Maggiori, Ola Svensson, David Wajc
2019	J	`jnl`	Perfect Matchings in Õ (n 1.5) Time in Regular Bipartite Graphs. Comb. Ashish Goel, Michael Kapralov, Sanjeev Khanna
2019	J	`jnl`	Practice of Streaming and Dynamic Graphs: Concepts, Models, Systems, and Parallelism. CoRR Maciej Besta, Marc Fischer, Vasiliki Kalavri, Michael Kapralov, Torsten Hoefler
2019	J	`jnl`	Space Efficient Approximation to Maximum Matching Size from Uniform Edge Samples. CoRR Michael Kapralov, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakab Tardos
2018	J	`jnl`	A Simple Sublinear-Time Algorithm for Counting Arbitrary Subgraphs via Edge Sampling. CoRR Sepehr Assadi, Michael Kapralov, Sanjeev Khanna
2018	J	`jnl`	A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms. CoRR Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2018	J	`jnl`	An Optimal Space Lower Bound for Approximating MAX-CUT. CoRR Michael Kapralov, Dmitry Krachun
2018	J	`jnl`	Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. CoRR Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2018	A*	`conf`	Testing Graph Clusterability: Algorithms and Lower Bounds. FOCS Ashish Chiplunkar, Michael Kapralov, Sanjeev Khanna, Aida Mousavifar, Yuval Peres
2018	J	`jnl`	Testing Graph Clusterability: Algorithms and Lower Bounds. CoRR Ashish Chiplunkar, Michael Kapralov, Sanjeev Khanna, Aida Mousavifar, Yuval Peres
2018	A*	`conf`	The Sketching Complexity of Graph and Hypergraph Counting. FOCS John Kallaugher, Michael Kapralov, Eric Price
2018	J	`jnl`	The Sketching Complexity of Graph and Hypergraph Counting. CoRR John Kallaugher, Michael Kapralov, Eric Price
2017	A*	`conf`	(1 + Ω(1))-Αpproximation to MAX-CUT Requires Linear Space. SODA Michael Kapralov, Sanjeev Khanna, Madhu Sudan, Ameya Velingker
2017	J	`jnl`	An Adaptive Sublinear-Time Block Sparse Fourier Transform. CoRR Volkan Cevher, Michael Kapralov, Jonathan Scarlett, Amir Zandieh
2017	A*	`conf`	An adaptive sublinear-time block sparse fourier transform. STOC Volkan Cevher, Michael Kapralov, Jonathan Scarlett, Amir Zandieh
2017	A*	`conf`	Optimal Lower Bounds for Universal Relation, and for Samplers and Finding Duplicates in Streams. FOCS Michael Kapralov, Jelani Nelson, Jakub Pachocki, Zhengyu Wang, David P. Woodruff, Mobin Yahyazadeh
2017	J	`jnl`	Optimal lower bounds for universal relation, and for samplers and finding duplicates in streams. CoRR Michael Kapralov, Jelani Nelson, Jakub Pachocki, Zhengyu Wang, David P. Woodruff, Mobin Yahyazadeh
2017	A*	`conf`	Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. ICML Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2017	A*	`conf`	Sample Efficient Estimation and Recovery in Sparse FFT via Isolation on Average. FOCS Michael Kapralov
2017	J	`jnl`	Sample Efficient Estimation and Recovery in Sparse FFT via Isolation on Average. CoRR Michael Kapralov
2017	J	`jnl`	Single Pass Spectral Sparsification in Dynamic Streams. SIAM J. Comput. Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford
2016	A*	`conf`	How to Fake Multiply by a Gaussian Matrix. ICML Michael Kapralov, Vamsi K. Potluru, David P. Woodruff
2016	J	`jnl`	How to Fake Multiply by a Gaussian Matrix. CoRR Michael Kapralov, Vamsi K. Potluru, David P. Woodruff
2016	J	`jnl`	Sparse Fourier Transform in Any Constant Dimension with Nearly-Optimal Sample Complexity in Sublinear Time. CoRR Michael Kapralov
2016	A*	`conf`	Sparse fourier transform in any constant dimension with nearly-optimal sample complexity in sublinear time. STOC Michael Kapralov
2016	A	`conf`	Subgraph Counting: Color Coding Beyond Trees. IPDPS Venkatesan T. Chakaravarthy, Michael Kapralov, Prakash Murali, Fabrizio Petrini, Xinyu Que, Yogish Sabharwal, Baruch Schieber
2016	J	`jnl`	Subgraph Counting: Color Coding Beyond Trees. CoRR Venkatesan T. Chakaravarthy, Michael Kapralov, Prakash Murali, Fabrizio Petrini, Xinyu Que, Yogish Sabharwal, Baruch Schieber
2015	A*	`conf`	Smooth Tradeoffs between Insert and Query Complexity in Nearest Neighbor Search. PODS Michael Kapralov
2015	A*	`conf`	Streaming Lower Bounds for Approximating MAX-CUT. SODA Michael Kapralov, Sanjeev Khanna, Madhu Sudan
2014	A*	`conf`	(Nearly) Sample-Optimal Sparse Fourier Transform. SODA Piotr Indyk, Michael Kapralov, Eric Price
2014	A*	`conf`	Approximating matching size from random streams. SODA Michael Kapralov, Sanjeev Khanna, Madhu Sudan
2014	J	`jnl`	Sample-Optimal Fourier Sampling in Any Constant Dimension - Part I. CoRR Piotr Indyk, Michael Kapralov
2014	A*	`conf`	Sample-Optimal Fourier Sampling in Any Constant Dimension. FOCS Piotr Indyk, Michael Kapralov
2014	A*	`conf`	Single Pass Spectral Sparsification in Dynamic Streams. FOCS Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford
2014	J	`jnl`	Single Pass Spectral Sparsification in Dynamic Streams. CoRR Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford
2014	A*	`conf`	Spanners and sparsifiers in dynamic streams. PODC Michael Kapralov, David P. Woodruff
2014	J	`jnl`	Streaming Lower Bounds for Approximating MAX-CUT. CoRR Michael Kapralov, Sanjeev Khanna, Madhu Sudan
2013	A*	`conf`	Better bounds for matchings in the streaming model. SODA Michael Kapralov
2013	A*	`conf`	On differentially private low rank approximation. SODA Michael Kapralov, Kunal Talwar
2013	A*	`conf`	Online Submodular Welfare Maximization: Greedy is Optimal. SODA Michael Kapralov, Ian Post, Jan Vondrák
2013	J	`jnl`	Perfect Matchings in O(nlog n) Time in Regular Bipartite Graphs. SIAM J. Comput. Ashish Goel, Michael Kapralov, Sanjeev Khanna
2012	A	`conf`	Embedding Paths into Trees: VM Placement to Minimize Congestion. ESA Debojyoti Dutta, Michael Kapralov, Ian Post, Rajendra Shinde
2012	J	`jnl`	Improved lower bounds for matchings in the streaming model CoRR Michael Kapralov
2012	—	`conf`	NNS Lower Bounds via Metric Expansion for l ∞ and EMD. ICALP (1) Michael Kapralov, Rina Panigrahy
2012	A*	`conf`	On the communication and streaming complexity of maximum bipartite matching. SODA Ashish Goel, Michael Kapralov, Sanjeev Khanna
2012	J	`jnl`	Optimal bandwidth-aware VM allocation for Infrastructure-as-a-Service CoRR Debojyoti Dutta, Michael Kapralov, Ian Post, Rajendra Shinde
2012	J	`jnl`	Single pass sparsification in the streaming model with edge deletions CoRR Ashish Goel, Michael Kapralov, Ian Post
2012	A	`conf`	Spectral sparsification via random spanners. ITCS Michael Kapralov, Rina Panigrahy
2011	—	`conf`	Multiplicative Approximations of Random Walk Transition Probabilities. APPROX-RANDOM Michael Kapralov, Rina Panigrahy
2011	—	`conf`	Prediction strategies without loss. NIPS Michael Kapralov, Rina Panigrahy
2010	J	`jnl`	Graph Sparsification via Refinement Sampling CoRR Ashish Goel, Michael Kapralov, Sanjeev Khanna
2010	—	`conf`	Improved Bounds for Online Stochastic Matching. ESA (1) Bahman Bahmani, Michael Kapralov
2010	A*	`conf`	Perfect matchings in o( STOC Ashish Goel, Michael Kapralov, Sanjeev Khanna
2010	J	`jnl`	Perfect matchings via uniform sampling in regular bipartite graphs. ACM Trans. Algorithms Ashish Goel, Michael Kapralov, Sanjeev Khanna
2010	J	`jnl`	Prediction strategies without loss CoRR Michael Kapralov, Rina Panigrahy
2009	—	`conf`	Factor Modeling for Advertisement Targeting. NIPS Ye Chen, Michael Kapralov, Dmitry Pavlov, John F. Canny
2009	J	`jnl`	Perfect Matchings in O(n \log n) Time in Regular Bipartite Graphs CoRR Ashish Goel, Michael Kapralov, Sanjeev Khanna
2009	A*	`conf`	Perfect matchings via uniform sampling in regular bipartite graphs. SODA Ashish Goel, Michael Kapralov, Sanjeev Khanna
2008	J	`jnl`	Perfect Matchings via Uniform Sampling in Regular Bipartite Graphs CoRR Ashish Goel, Michael Kapralov, Sanjeev Khanna