Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDRichard Peng
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2021
[c55]Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, Chi Wang:
LightNE: A Lightweight Graph Processing System for Network Embedding. SIGMOD Conference 2021: 2281-2289- [c54]Richard Peng, Santosh S. Vempala:
Solving Sparse Linear Systems Faster than Matrix Multiplication. SODA 2021: 504-521 - [c53]Parinya Chalermsook, Syamantak Das, Yunbum Kook, Bundit Laekhanukit, Yang P. Liu, Richard Peng, Mark Sellke, Daniel Vaz:
Vertex Sparsification for Edge Connectivity. SODA 2021: 1206-1225 - [i66]Yu Gao, Yang P. Liu, Richard Peng:
Fully Dynamic Electrical Flows: Sparse Maxflow Faster Than Goldberg-Rao. CoRR abs/2101.07233 (2021) - [i65]Li Chen, Richard Peng, Di Wang:
𝓁2-norm Flow Diffusion in Near-Linear Time. CoRR abs/2105.14629 (2021) - 2020
- [j8]David Durfee, John Peebles, Richard Peng, Anup B. Rao:
Determinant-Preserving Sparsification of SDDM Matrices. SIAM J. Comput. 49(4) (2020) - [c52]Jan van den Brand, Yin Tat Lee, Danupon Nanongkai, Richard Peng, Thatchaphol Saranurak
, Aaron Sidford, Zhao Song, Di Wang:
Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs. FOCS 2020: 919-930 - [c51]Li Chen, Gramoz Goranci, Monika Henzinger, Richard Peng, Thatchaphol Saranurak:
Fast Dynamic Cuts, Distances and Effective Resistances via Vertex Sparsifiers. FOCS 2020: 1135-1146 - [c50]Julia Chuzhoy, Yu Gao, Jason Li, Danupon Nanongkai, Richard Peng, Thatchaphol Saranurak:
A Deterministic Algorithm for Balanced Cut with Applications to Dynamic Connectivity, Flows, and Beyond. FOCS 2020: 1158-1167 - [c49]Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang:
Faster Graph Embeddings via Coarsening. ICML 2020: 2953-2963 - [c48]Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, Jie Tang:
A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices. NeurIPS 2020 - [c47]Laxman Dhulipala, David Durfee, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, Xiaorui Sun:
Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds. SODA 2020: 1300-1319 - [c46]Digvijay Boob, Yu Gao, Richard Peng, Saurabh Sawlani, Charalampos E. Tsourakakis, Di Wang, Junxing Wang:
Flowless: Extracting Densest Subgraphs Without Flow Computations. WWW 2020: 573-583 - [i64]Yihe Dong, Yu Gao, Richard Peng, Ilya P. Razenshteyn, Saurabh Sawlani:
A Study of Performance of Optimal Transport. CoRR abs/2005.01182 (2020) - [i63]Li Chen, Gramoz Goranci, Monika Henzinger, Richard Peng, Thatchaphol Saranurak:
Fast Dynamic Cuts, Distances and Effective Resistances via Vertex Sparsifiers. CoRR abs/2005.02368 (2020) - [i62]Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang:
Faster Graph Embeddings via Coarsening. CoRR abs/2007.02817 (2020) - [i61]Parinya Chalermsook, Syamantak Das, Bundit Laekhanukit, Yunbum Kook, Yang P. Liu, Richard Peng, Mark Sellke, Daniel Vaz:
Vertex Sparsification for Edge Connectivity. CoRR abs/2007.07862 (2020) - [i60]Richard Peng, Santosh S. Vempala:
Solving Sparse Linear Systems Faster than Matrix Multiplication. CoRR abs/2007.10254 (2020) - [i59]Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, Jie Tang:
Concentration Bounds for Co-occurrence Matrices of Markov Chains. CoRR abs/2008.02464 (2020) - [i58]Jan van den Brand, Yin Tat Lee, Danupon Nanongkai, Richard Peng, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang:
Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs. CoRR abs/2009.01802 (2020) - [i57]Sebastian Forster, Gramoz Goranci, Yang P. Liu, Richard Peng, Xiaorui Sun, Mingquan Ye:
Minor Sparsifiers and the Distributed Laplacian Paradigm. CoRR abs/2012.15675 (2020)
2010 – 2019
- 2019
- [c45]Deeksha Adil, Richard Peng, Sushant Sachdeva:
Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression. NeurIPS 2019: 14166-14177 - [c44]Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva:
Iterative Refinement for ℓp-norm Regression. SODA 2019: 1405-1424 - [c43]Rasmus Kyng, Richard Peng, Sushant Sachdeva, Di Wang:
Flows in almost linear time via adaptive preconditioning. STOC 2019: 902-913 - [c42]David Durfee, Yu Gao, Gramoz Goranci, Richard Peng:
Fully dynamic spectral vertex sparsifiers and applications. STOC 2019: 914-925 - [c41]Richard Peng, Bryce Sandlund, Daniel Dominic Sleator:
Optimal Offline Dynamic 2, 3-Edge/Vertex Connectivity. WADS 2019: 553-565 - [c40]Huan Li, Richard Peng, Liren Shan, Yuhao Yi, Zhongzhi Zhang:
Current Flow Group Closeness Centrality for Complex Networks? WWW 2019: 961-971 - [i56]Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva:
Iterative Refinement for 𝓁p-norm Regression. CoRR abs/1901.06764 (2019) - [i55]Brian Bullins, Richard Peng:
Higher-Order Accelerated Methods for Faster Non-Smooth Optimization. CoRR abs/1906.01621 (2019) - [i54]Rasmus Kyng, Richard Peng, Sushant Sachdeva, Di Wang:
Flows in Almost Linear Time via Adaptive Preconditioning. CoRR abs/1906.10340 (2019) - [i53]David Durfee, Yu Gao, Gramoz Goranci, Richard Peng:
Fully Dynamic Spectral Vertex Sparsifiers and Applications. CoRR abs/1906.10530 (2019) - [i52]Deeksha Adil, Richard Peng, Sushant Sachdeva:
Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression. CoRR abs/1907.07167 (2019) - [i51]J. Ian Munro, Richard Peng, Sebastian Wild, Lingyi Zhang:
Dynamic Optimality Refuted - For Tournament Heaps. CoRR abs/1908.00563 (2019) - [i50]David Durfee, Laxman Dhulipala, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, Xiaorui Sun:
Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds. CoRR abs/1908.01956 (2019) - [i49]Digvijay Boob, Yu Gao, Richard Peng, Saurabh Sawlani, Charalampos E. Tsourakakis, Di Wang, Junxing Wang:
Flowless: Extracting Densest Subgraphs Without Flow Computations. CoRR abs/1910.07087 (2019) - [i48]Yu Gao, Jason Li, Danupon Nanongkai, Richard Peng, Thatchaphol Saranurak, Sorrachai Yingchareonthawornchai:
Deterministic Graph Cuts in Subquadratic Time: Sparse, Balanced, and k-Vertex. CoRR abs/1910.07950 (2019) - [i47]Julia Chuzhoy, Yu Gao, Jason Li, Danupon Nanongkai, Richard Peng, Thatchaphol Saranurak:
A Deterministic Algorithm for Balanced Cut with Applications to Dynamic Connectivity, Flows, and Beyond. CoRR abs/1910.08025 (2019) - [i46]Yang P. Liu, Richard Peng, Mark Sellke:
Vertex Sparsifiers for c-Edge Connectivity. CoRR abs/1910.10359 (2019) - 2018
- [c39]Meng He, Richard Peng, Yinzhan Xu:
Parameterizing the Hardness of Binary Search Tree Access Sequences by Inversion Counts. ANALCO 2018: 32-39 - [c38]Matthew Fahrbach, Gary L. Miller, Richard Peng, Saurabh Sawlani, Junxing Wang, Shen Chen Xu:
Graph Sketching against Adaptive Adversaries Applied to the Minimum Degree Algorithm. FOCS 2018: 101-112 - [c37]Timothy Chu, Yu Gao, Richard Peng, Sushant Sachdeva, Saurabh Sawlani, Junxing Wang:
Graph Sparsification, Spectral Sketches, and Faster Resistance Computation, via Short Cycle Decompositions. FOCS 2018: 361-372 - [c36]Michael B. Cohen, Jonathan A. Kelner, Rasmus Kyng, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford:
Solving Directed Laplacian Systems in Nearly-Linear Time through Sparse LU Factorizations. FOCS 2018: 898-909 - [c35]Rasmus Kyng, Richard Peng, Robert Schwieterman, Peng Zhang:
Incomplete nested dissection. STOC 2018: 404-417 - [i45]Huan Li, Richard Peng, Liren Shan, Yuhao Yi, Zhongzhi Zhang:
Current Flow Group Closeness Centrality for Complex Networks. CoRR abs/1802.02556 (2018) - [i44]David Durfee, Yu Gao, Gramoz Goranci, Richard Peng:
Fully Dynamic Effective Resistances. CoRR abs/1804.04038 (2018) - [i43]Matthew Fahrbach, Gary L. Miller, Richard Peng, Saurabh Sawlani, Junxing Wang, Shen Chen Xu:
Graph Sketching Against Adaptive Adversaries Applied to the Minimum Degree Algorithm. CoRR abs/1804.04239 (2018) - [i42]Rasmus Kyng, Richard Peng, Robert Schwieterman, Peng Zhang:
Incomplete Nested Dissection. CoRR abs/1805.09442 (2018) - [i41]Timothy Chu, Yu Gao, Richard Peng, Sushant Sachdeva, Saurabh Sawlani, Junxing Wang:
Graph Sparsification, Spectral Sketches, and Faster Resistance Computation, via Short Cycle Decompositions. CoRR abs/1805.12051 (2018) - [i40]Timothy Chu, Michael B. Cohen, Jakub W. Pachocki, Richard Peng:
Constant Arboricity Spectral Sparsifiers. CoRR abs/1808.05662 (2018) - [i39]Michael B. Cohen, Jonathan A. Kelner, Rasmus Kyng, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford:
Solving Directed Laplacian Systems in Nearly-Linear Time through Sparse LU Factorizations. CoRR abs/1811.10722 (2018) - [i38]Henning Meyerhenke, Richard Peng, Ilya Safro:
High-Performance Graph Algorithms (Dagstuhl Seminar 18241). Dagstuhl Reports 8(6): 19-39 (2018) - 2017
- [j7]Richard Peng, He Sun, Luca Zanetti:
Partitioning Well-Clustered Graphs: Spectral Clustering Works! SIAM J. Comput. 46(2): 710-743 (2017) - [c34]Gorav Jindal, Pavel Kolev, Richard Peng, Saurabh Sawlani:
Density Independent Algorithms for Sparsifying k-Step Random Walks. APPROX-RANDOM 2017: 14:1-14:17 - [c33]David Durfee, John Peebles, Richard Peng, Anup B. Rao:
Determinant-Preserving Sparsification of SDDM Matrices with Applications to Counting and Sampling Spanning Trees. FOCS 2017: 926-937 - [c32]Rasmus Kyng, Jakub Pachocki, Richard Peng, Sushant Sachdeva:
A Framework for Analyzing Resparsification Algorithms. SODA 2017: 2032-2043 - [c31]Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford, Adrian Vladu:
Almost-linear-time algorithms for Markov chains and new spectral primitives for directed graphs. STOC 2017: 410-419 - [i37]Gorav Jindal, Pavel Kolev, Richard Peng, Saurabh Sawlani:
Density Independent Algorithms for Sparsifying k-Step Random Walks. CoRR abs/1702.06110 (2017) - [i36]Tung Mai, Richard Peng, Anup B. Rao, Vijay V. Vazirani:
Concave Flow on Small Depth Directed Networks. CoRR abs/1704.07791 (2017) - [i35]David Durfee, John Peebles, Richard Peng, Anup B. Rao:
Determinant-Preserving Sparsification of SDDM Matrices with Applications to Counting and Sampling Spanning Trees. CoRR abs/1705.00985 (2017) - [i34]Richard Peng, Bryce Sandlund, Daniel Dominic Sleator:
Offline Dynamic Higher Connectivity. CoRR abs/1708.03812 (2017) - [i33]Matthew Fahrbach, Gary L. Miller, Richard Peng, Saurabh Sawlani, Junxing Wang, Shen Chen Xu:
On Computing Min-Degree Elimination Orderings. CoRR abs/1711.08446 (2017) - 2016
- [j6]Ioannis Koutis, Alex Levin, Richard Peng:
Faster Spectral Sparsification and Numerical Algorithms for SDD Matrices. ACM Trans. Algorithms 12(2): 17:1-17:16 (2016) - [c30]Mihai Cucuringu, Ioannis Koutis, Sanjay Chawla, Gary L. Miller, Richard Peng:
Simple and Scalable Constrained Clustering: a Generalized Spectral Method. AISTATS 2016: 445-454 - [c29]Ittai Abraham, David Durfee, Ioannis Koutis, Sebastian Krinninger, Richard Peng:
On Fully Dynamic Graph Sparsifiers. FOCS 2016: 335-344 - [c28]Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Aaron Sidford, Adrian Vladu:
Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More. FOCS 2016: 583-592 - [c27]Dehua Cheng, Richard Peng, Yan Liu, Ioakeim Perros:
SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling. NIPS 2016: 721-729 - [c26]Kevin Deweese, John R. Gilbert, Gary L. Miller, Richard Peng, Hao Ran Xu, Shen Chen Xu:
An Empirical Study of Cycle Toggling Based Laplacian Solvers. CSC 2016: 33-41 - [c25]Richard Peng:
Approximate Undirected Maximum Flows in O(mpolylog(n)) Time. SODA 2016: 1862-1867 - [c24]Rasmus Kyng, Yin Tat Lee, Richard Peng, Sushant Sachdeva, Daniel A. Spielman:
Sparsified Cholesky and multigrid solvers for connection laplacians. STOC 2016: 842-850 - [i32]Mihai Cucuringu, Ioannis Koutis, Sanjay Chawla, Gary L. Miller, Richard Peng:
Scalable Constrained Clustering: A Generalized Spectral Method. CoRR abs/1601.04746 (2016) - [i31]Ittai Abraham, David Durfee, Ioannis Koutis, Sebastian Krinninger, Richard Peng:
On Fully Dynamic Graph Sparsifiers. CoRR abs/1604.02094 (2016) - [i30]Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Aaron Sidford, Adrian Vladu:
Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More. CoRR abs/1608.03270 (2016) - [i29]Kevin Deweese, John R. Gilbert, Gary L. Miller, Richard Peng, Hao Ran Xu, Shen Chen Xu:
An Empirical Study of Cycle Toggling Based Laplacian Solvers. CoRR abs/1609.02957 (2016) - [i28]Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford, Adrian Vladu:
Almost-Linear-Time Algorithms for Markov Chains and New Spectral Primitives for Directed Graphs. CoRR abs/1611.00755 (2016) - [i27]Rasmus Kyng, Jakub Pachocki, Richard Peng, Sushant Sachdeva:
A Framework for Analyzing Resparsification Algorithms. CoRR abs/1611.06940 (2016) - 2015
- [c23]Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng:
Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification. COLT 2015: 364-390 - [c22]Richard Peng, He Sun, Luca Zanetti:
Partitioning Well-Clustered Graphs: Spectral Clustering Works! COLT 2015: 1423-1455 - [c21]Michael B. Cohen, Yin Tat Lee, Cameron Musco, Christopher Musco, Richard Peng, Aaron Sidford:
Uniform Sampling for Matrix Approximation. ITCS 2015: 181-190 - [c20]Michael Mitzenmacher, Jakub Pachocki, Richard Peng, Charalampos E. Tsourakakis, Shen Chen Xu:
Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling. KDD 2015: 815-824 - [c19]Gary L. Miller, Richard Peng, Adrian Vladu, Shen Chen Xu:
Improved Parallel Algorithms for Spanners and Hopsets. SPAA 2015: 192-201 - [c18]Michael B. Cohen, Richard Peng:
Lp Row Sampling by Lewis Weights. STOC 2015: 183-192 - [i26]Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng:
Spectral Sparsification of Random-Walk Matrix Polynomials. CoRR abs/1502.03496 (2015) - [i25]Yin Tat Lee, Richard Peng, Daniel A. Spielman:
Sparsified Cholesky Solvers for SDD linear systems. CoRR abs/1506.08204 (2015) - [i24]Rasmus Kyng, Yin Tat Lee, Richard Peng, Sushant Sachdeva, Daniel A. Spielman:
Sparsified Cholesky and Multigrid Solvers for Connection Laplacians. CoRR abs/1512.01892 (2015) - 2014
- [j5]Guy E. Blelloch, Anupam Gupta, Ioannis Koutis, Gary L. Miller, Richard Peng, Kanat Tangwongsan:
Nearly-Linear Work Parallel SDD Solvers, Low-Diameter Decomposition, and Low-Stretch Subgraphs. Theory Comput. Syst. 55(3): 521-554 (2014) - [j4]Ioannis Koutis, Gary L. Miller, Richard Peng:
Approaching Optimality for Solving SDD Linear Systems. SIAM J. Comput. 43(1): 337-354 (2014) - [c17]Michael B. Cohen, Brittany Terese Fasy, Gary L. Miller, Amir Nayyeri, Richard Peng, Noel Walkington:
Solving 1-Laplacians in Nearly Linear Time: Collapsing and Expanding a Topological Ball. SODA 2014: 204-216 - [c16]Richard Peng, Daniel A. Spielman:
An efficient parallel solver for SDD linear systems. STOC 2014: 333-342 - [c15]Michael B. Cohen, Rasmus Kyng, Gary L. Miller, Jakub W. Pachocki, Richard Peng, Anup B. Rao, Shen Chen Xu:
Solving SDD linear systems in nearly mlog1/2n time. STOC 2014: 343-352 - [i23]Michael B. Cohen, Gary L. Miller, Jakub W. Pachocki, Richard Peng, Shen Chen Xu:
Stretching Stretch. CoRR abs/1401.2454 (2014) - [i22]Michael B. Cohen, Rasmus Kyng, Jakub W. Pachocki, Richard Peng, Anup B. Rao:
Preconditioning in Expectation. CoRR abs/1401.6236 (2014) - [i21]Michael B. Cohen, Yin Tat Lee, Cameron Musco, Christopher Musco, Richard Peng, Aaron Sidford:
Uniform Sampling for Matrix Approximation. CoRR abs/1408.5099 (2014) - [i20]Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng:
Scalable Parallel Factorizations of SDD Matrices and Efficient Sampling for Gaussian Graphical Models. CoRR abs/1410.5392 (2014) - [i19]Richard Peng, He Sun, Luca Zanetti:
Partitioning Well-Clustered Graphs with k-Means and Heat Kernel. CoRR abs/1411.2021 (2014) - [i18]Richard Peng:
A Note on Cut-Approximators and Approximating Undirected Max Flows. CoRR abs/1411.7631 (2014) - [i17]Michael B. Cohen, Richard Peng:
ℓp Row Sampling by Lewis Weights. CoRR abs/1412.0588 (2014) - [i16]Ioannis Koutis, Gary L. Miller, Richard Peng:
A Generalized Cheeger Inequality. CoRR abs/1412.6075 (2014) - 2013
- [c14]Mu Li, Gary L. Miller, Richard Peng:
Iterative Row Sampling. FOCS 2013: 127-136 - [c13]Manoj Gupta, Richard Peng:
Fully Dynamic (1+ e)-Approximate Matchings. FOCS 2013: 548-557 - [c12]Hui Han Chin, Aleksander Madry, Gary L. Miller, Richard Peng:
Runtime guarantees for regression problems. ITCS 2013: 269-282 - [c11]Gary L. Miller, Richard Peng:
Approximate Maximum Flow on Separable Undirected Graphs. SODA 2013: 1151-1170 - [c10]Gary L. Miller, Richard Peng, Shen Chen Xu:
Parallel graph decompositions using random shifts. SPAA 2013: 196-203 - [i15]Manoj Gupta, Richard Peng:
Fully Dynamic $(1+ε)$-Approximate Matchings. CoRR abs/1304.0378 (2013) - [i14]Gary L. Miller, Richard Peng, Shen Chen Xu:
Parallel Graph Decompositions Using Random Shifts. CoRR abs/1307.3692 (2013) - [i13]Gary L. Miller, Richard Peng, Shen Chen Xu:
Parallel Algorithms for Approximate Undirected Shortest Paths in $m\log^{3+α}n$ Work. CoRR abs/1309.3545 (2013) - [i12]Richard Peng, Daniel A. Spielman:
An Efficient Parallel Solver for SDD Linear Systems. CoRR abs/1311.3286 (2013) - 2012
- [j3]Ioannis Koutis, Gary L. Miller, Richard Peng:
A fast solver for a class of linear systems. Commun. ACM 55(10): 99-107 (2012) - [j2]Mihail N. Kolountzakis, Gary L. Miller, Richard Peng, Charalampos E. Tsourakakis:
Efficient Triangle Counting in Large Graphs via Degree-Based Vertex Partitioning. Internet Math. 8(1-2): 161-185 (2012) - [c9]Richard Peng, Kanat Tangwongsan:
Faster and simpler width-independent parallel algorithms for positive semidefinite programming. SPAA 2012: 101-108 - [c8]Ioannis Koutis, Alex Levin, Richard Peng:
Improved Spectral Sparsification and Numerical Algorithms for SDD Matrices. STACS 2012: 266-277 - [c7]Jonathan A. Kelner, Gary L. Miller, Richard Peng:
Faster approximate multicommodity flow using quadratically coupled flows. STOC 2012: 1-18 - [i11]Richard Peng, Kanat Tangwongsan:
Faster and Simpler Width-Independent Parallel Algorithms for Positive Semidefinite Programming. CoRR abs/1201.5135 (2012) - [i10]Jonathan A. Kelner, Gary L. Miller, Richard Peng:
Faster Approximate Multicommodity Flow Using Quadratically Coupled Flows. CoRR abs/1202.3367 (2012) - [i9]Ioannis Koutis, Alex Levin, Richard Peng:
Faster spectral sparsification and numerical algorithms for SDD matrices. CoRR abs/1209.5821 (2012) - [i8]Gary L. Miller, Richard Peng:
Approximate Maximum Flow on Separable Undirected Graphs. CoRR abs/1210.5227 (2012) - [i7]Gary L. Miller, Richard Peng:
Iterative Approaches to Row Sampling. CoRR abs/1211.2713 (2012) - 2011
- [j1]Charalampos E. Tsourakakis, Richard Peng, Maria A. Tsiarli, Gary L. Miller, Russell Schwartz:
Approximation algorithms for speeding up dynamic programming and denoising aCGH data. ACM J. Exp. Algorithmics 16 (2011) - [c6]Ioannis Koutis, Gary L. Miller, Richard Peng:
A Nearly-m log n Time Solver for SDD Linear Systems. FOCS 2011: 590-598 - [c5]Gary L. Miller, Richard Peng, Russell Schwartz, Charalampos E. Tsourakakis:
Approximate Dynamic Programming using Halfspace Queries and Multiscale Monge Decomposition. SODA 2011: 1675-1682 - [c4]Guy E. Blelloch, Anupam Gupta, Ioannis Koutis, Gary L. Miller, Richard Peng, Kanat Tangwongsan:
Near linear-work parallel SDD solvers, low-diameter decomposition, and low-stretch subgraphs. SPAA 2011: 13-22 - [c3]Guy E. Blelloch, Richard Peng, Kanat Tangwongsan:
Linear-work greedy parallel approximate set cover and variants. SPAA 2011: 23-32 - [i6]Ioannis Koutis, Gary L. Miller, Richard Peng:
Solving SDD linear systems in time Õ(mlog nlog(1/ε)). CoRR abs/1102.4842 (2011) - [i5]Aleksander Madry, Gary L. Miller, Richard Peng:
Electrical Flow Algorithms for Total Variation Minimization. CoRR abs/1110.1358 (2011) - [i4]Guy E. Blelloch, Anupam Gupta, Ioannis Koutis, Gary L. Miller, Richard Peng, Kanat Tangwongsan:
Near Linear-Work Parallel SDD Solvers, Low-Diameter Decomposition, and Low-Stretch Subgraphs. CoRR abs/1111.1750 (2011) - 2010
- [c2]Ioannis Koutis, Gary L. Miller, Richard Peng:
Approaching Optimality for Solving SDD Linear Systems. FOCS 2010: 235-244 - [c1]Mihail N. Kolountzakis, Gary L. Miller, Richard Peng, Charalampos E. Tsourakakis:
Efficient Triangle Counting in Large Graphs via Degree-Based Vertex Partitioning. WAW 2010: 15-24 - [i3]Ioannis Koutis, Gary L. Miller, Richard Peng:
Approaching optimality for solving SDD systems. CoRR abs/1003.2958 (2010) - [i2]Gary L. Miller, Richard Peng, Russell Schwartz, Charalampos E. Tsourakakis:
Approximate Dynamic Programming for Fast Denoising of aCGH Data. CoRR abs/1003.4942 (2010) - [i1]Mihail N. Kolountzakis, Gary L. Miller, Richard Peng, Charalampos E. Tsourakakis:
Efficient Triangle Counting in Large Graphs via Degree-based Vertex Partitioning. CoRR abs/1011.0468 (2010)
Coauthor Index