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Raghu Meka
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2020 – today
- 2024
- [c68]Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka:
Learning Neural Networks with Sparse Activations. COLT 2024: 406-425 - [c67]Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis, Raghu Meka, Konstantinos Stavropoulos:
Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension. COLT 2024: 876-922 - [c66]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
On Convex Optimization with Semi-Sensitive Features. COLT 2024: 1916-1938 - [c65]Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps. COLT 2024: 2840-2886 - [c64]Amir Abboud
, Nick Fischer
, Zander Kelley
, Shachar Lovett
, Raghu Meka
:
New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms. STOC 2024: 935-943 - [c63]Zander Kelley
, Shachar Lovett
, Raghu Meka
:
Explicit Separations between Randomized and Deterministic Number-on-Forehead Communication. STOC 2024: 1299-1310 - [i77]Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps. CoRR abs/2402.15409 (2024) - [i76]Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka:
Learning Neural Networks with Sparse Activations. CoRR abs/2406.17989 (2024) - [i75]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
On Convex Optimization with Semi-Sensitive Features. CoRR abs/2406.19040 (2024) - [i74]Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis, Raghu Meka, Konstantinos Stavropoulos:
Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension. CoRR abs/2407.00966 (2024) - 2023
- [c62]Sitan Chen, Zehao Dou, Surbhi Goel, Adam R. Klivans, Raghu Meka:
Learning Narrow One-Hidden-Layer ReLU Networks. COLT 2023: 5580-5614 - [c61]Nishanth Dikkala, Nikhil Ghosh, Raghu Meka, Rina Panigrahy, Nikhil Vyas, Xin Wang:
On the Benefits of Learning to Route in Mixture-of-Experts Models. EMNLP 2023: 9376-9396 - [c60]Zander Kelley, Raghu Meka:
Strong Bounds for 3-Progressions. FOCS 2023: 933-973 - [c59]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
On User-Level Private Convex Optimization. ICML 2023: 11283-11299 - [c58]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
User-Level Differential Privacy With Few Examples Per User. NeurIPS 2023 - [c57]Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Feature Adaptation for Sparse Linear Regression. NeurIPS 2023 - [c56]Peter Ivanov, Raghu Meka, Emanuele Viola:
Efficient resilient functions. SODA 2023: 2867-2874 - [c55]Nikhil Bansal, Haotian Jiang, Raghu Meka:
Resolving Matrix Spencer Conjecture Up to Poly-logarithmic Rank. STOC 2023: 1814-1819 - [i73]Sitan Chen, Zehao Dou, Surbhi Goel, Adam R. Klivans, Raghu Meka:
Learning Narrow One-Hidden-Layer ReLU Networks. CoRR abs/2304.10524 (2023) - [i72]Badih Ghazi, Pritish Kamath, Ravi Kumar, Raghu Meka, Pasin Manurangsi, Chiyuan Zhang:
On User-Level Private Convex Optimization. CoRR abs/2305.04912 (2023) - [i71]Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Feature Adaptation for Sparse Linear Regression. CoRR abs/2305.16892 (2023) - [i70]Zander Kelley, Shachar Lovett, Raghu Meka:
Explicit separations between randomized and deterministic Number-on-Forehead communication. CoRR abs/2308.12451 (2023) - [i69]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
User-Level Differential Privacy With Few Examples Per User. CoRR abs/2309.12500 (2023) - [i68]Yuanzhi Li, Raghu Meka, Rina Panigrahy, Kulin Shah:
Simple Mechanisms for Representing, Indexing and Manipulating Concepts. CoRR abs/2310.12143 (2023) - [i67]Amir Abboud, Nick Fischer, Zander Kelley, Shachar Lovett, Raghu Meka:
New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms. CoRR abs/2311.09095 (2023) - [i66]Amir Abboud, Nick Fischer, Zander Kelley, Shachar Lovett, Raghu Meka:
New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms. Electron. Colloquium Comput. Complex. TR23 (2023) - [i65]Zander Kelley, Shachar Lovett, Raghu Meka:
Explicit separations between randomized and deterministic Number-on-Forehead communication. Electron. Colloquium Comput. Complex. TR23 (2023) - 2022
- [j16]Pravesh K. Kothari, Raghu Meka, Prasad Raghavendra:
Approximating Rectangles by Juntas and Weakly Exponential Lower Bounds for LP Relaxations of CSPs. SIAM J. Comput. 51(2): 17-305 (2022) - [c54]Zander Kelley, Raghu Meka:
Random Restrictions and PRGs for PTFs in Gaussian Space. CCC 2022: 21:1-21:24 - [c53]Nikhil Bansal, Haotian Jiang, Raghu Meka, Sahil Singla, Makrand Sinha:
Smoothed Analysis of the Komlós Conjecture. ICALP 2022: 14:1-14:12 - [c52]Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka:
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs. ICLR 2022 - [c51]Nikhil Bansal, Haotian Jiang, Raghu Meka, Sahil Singla, Makrand Sinha:
Prefix Discrepancy, Smoothed Analysis, and Combinatorial Vector Balancing. ITCS 2022: 13:1-13:22 - [c50]Shachar Lovett, Raghu Meka, Ian Mertz
, Toniann Pitassi, Jiapeng Zhang:
Lifting with Sunflowers. ITCS 2022: 104:1-104:24 - [c49]Sitan Chen, Aravind Gollakota, Adam R. Klivans, Raghu Meka:
Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks. NeurIPS 2022 - [c48]Nishanth Dikkala, Sankeerth Rao Karingula, Raghu Meka, Jelani Nelson, Rina Panigrahy, Xin Wang:
Sketching based Representations for Robust Image Classification with Provable Guarantees. NeurIPS 2022 - [c47]Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs. NeurIPS 2022 - [i64]Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka:
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs. CoRR abs/2201.07206 (2022) - [i63]Sitan Chen, Aravind Gollakota, Adam R. Klivans, Raghu Meka:
Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks. CoRR abs/2202.05258 (2022) - [i62]Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Distributional Hardness Against Preconditioned Lasso via Erasure-Robust Designs. CoRR abs/2203.02824 (2022) - [i61]Nikhil Bansal, Haotian Jiang, Raghu Meka, Sahil Singla, Makrand Sinha:
Smoothed Analysis of the Komlós Conjecture. CoRR abs/2204.11427 (2022) - [i60]Nikhil Bansal, Haotian Jiang, Raghu Meka:
Resolving Matrix Spencer Conjecture Up to Poly-logarithmic Rank. CoRR abs/2208.11286 (2022) - [i59]Peter Ivanov, Raghu Meka, Emanuele Viola:
Efficient resilient functions. Electron. Colloquium Comput. Complex. TR22 (2022) - 2021
- [c46]Dean Doron
, Raghu Meka, Omer Reingold, Avishay Tal, Salil P. Vadhan:
Pseudorandom Generators for Read-Once Monotone Branching Programs. APPROX-RANDOM 2021: 58:1-58:21 - [c45]Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
On the Power of Preconditioning in Sparse Linear Regression. FOCS 2021: 550-561 - [c44]Sitan Chen, Adam R. Klivans, Raghu Meka:
Learning Deep ReLU Networks Is Fixed-Parameter Tractable. FOCS 2021: 696-707 - [c43]Sitan Chen, Adam R. Klivans, Raghu Meka:
Efficiently Learning One Hidden Layer ReLU Networks From Queries. NeurIPS 2021: 24087-24098 - [c42]Nikhil Bansal, Haotian Jiang, Raghu Meka, Sahil Singla, Makrand Sinha:
Online Discrepancy Minimization for Stochastic Arrivals. SODA 2021: 2842-2861 - [i58]Zander Kelley, Raghu Meka:
Random restrictions and PRGs for PTFs in Gaussian Space. CoRR abs/2103.14134 (2021) - [i57]Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
On the Power of Preconditioning in Sparse Linear Regression. CoRR abs/2106.09207 (2021) - [i56]Sitan Chen, Adam R. Klivans, Raghu Meka:
Efficiently Learning Any One Hidden Layer ReLU Network From Queries. CoRR abs/2111.04727 (2021) - [i55]Nikhil Bansal, Haotian Jiang, Raghu Meka, Sahil Singla, Makrand Sinha:
Prefix Discrepancy, Smoothed Analysis, and Combinatorial Vector Balancing. CoRR abs/2111.07049 (2021) - [i54]Dean Doron, Raghu Meka, Omer Reingold, Avishay Tal, Salil P. Vadhan:
Monotone Branching Programs: Pseudorandomness and Circuit Complexity. Electron. Colloquium Comput. Complex. TR21 (2021) - [i53]Zander Kelley, Raghu Meka:
Random restrictions and PRGs for PTFs in Gaussian Space. Electron. Colloquium Comput. Complex. TR21 (2021) - 2020
- [j15]Nikhil Bansal, Raghu Meka:
On the discrepancy of random low degree set systems. Random Struct. Algorithms 57(3): 695-705 (2020) - [c41]Sitan Chen, Raghu Meka:
Learning Polynomials in Few Relevant Dimensions. COLT 2020: 1161-1227 - [c40]Paxton Turner, Raghu Meka, Philippe Rigollet:
Balancing Gaussian vectors in high dimension. COLT 2020: 3455-3486 - [c39]Eshan Chattopadhyay, Jesse Goodman, Vipul Goyal, Ashutosh Kumar, Xin Li, Raghu Meka, David Zuckerman:
Extractors and Secret Sharing Against Bounded Collusion Protocols. FOCS 2020: 1226-1242 - [c38]Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Ankur Moitra:
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds. NeurIPS 2020 - [e1]Jaroslaw Byrka
, Raghu Meka:
Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2020, August 17-19, 2020, Virtual Conference. LIPIcs 176, Schloss Dagstuhl - Leibniz-Zentrum für Informatik 2020, ISBN 978-3-95977-164-1 [contents] - [i52]Sitan Chen, Raghu Meka:
Learning Polynomials of Few Relevant Dimensions. CoRR abs/2004.13748 (2020) - [i51]Nikhil Bansal, Haotian Jiang, Raghu Meka, Sahil Singla, Makrand Sinha:
Online Discrepancy Minimization for Stochastic Arrivals. CoRR abs/2007.10622 (2020) - [i50]Sitan Chen, Adam R. Klivans, Raghu Meka:
Learning Deep ReLU Networks Is Fixed-Parameter Tractable. CoRR abs/2009.13512 (2020) - [i49]Ashutosh Kumar, Raghu Meka, David Zuckerman:
Bounded Collusion Protocols, Cylinder-Intersection Extractors and Leakage-Resilient Secret Sharing. Electron. Colloquium Comput. Complex. TR20 (2020) - [i48]Shachar Lovett, Raghu Meka, Jiapeng Zhang:
Improved lifting theorems via robust sunflowers. Electron. Colloquium Comput. Complex. TR20 (2020) - [i47]Ashutosh Kumar, Raghu Meka, David Zuckerman:
Bounded Collusion Protocols, Cylinder-Intersection Extractors and Leakage-Resilient Secret Sharing. IACR Cryptol. ePrint Arch. 2020: 473 (2020)
2010 – 2019
- 2019
- [j14]Russell Impagliazzo
, Raghu Meka, David Zuckerman:
Pseudorandomness from Shrinkage. J. ACM 66(2): 11:1-11:16 (2019) - [c37]Ashutosh Kumar, Raghu Meka, Amit Sahai:
Leakage-Resilient Secret Sharing Against Colluding Parties. FOCS 2019: 636-660 - [c36]Nikhil Bansal, Raghu Meka:
On the discrepancy of random low degree set systems. SODA 2019: 2557-2564 - [c35]Raghu Meka, Omer Reingold, Avishay Tal:
Pseudorandom generators for width-3 branching programs. STOC 2019: 626-637 - [i46]Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Ankur Moitra:
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds. CoRR abs/1905.01282 (2019) - [i45]Raghu Meka, Philippe Rigollet, Paxton Turner:
Balancing Gaussian vectors in high dimension. CoRR abs/1910.13972 (2019) - [i44]Arnab Bhattacharyya, Philips George John, Suprovat Ghoshal, Raghu Meka:
Average Bias and Polynomial Sources. Electron. Colloquium Comput. Complex. TR19 (2019) - 2018
- [j13]Parikshit Gopalan, Daniel M. Kane, Raghu Meka:
Pseudorandomness via the Discrete Fourier Transform. SIAM J. Comput. 47(6): 2451-2487 (2018) - [c34]Adam R. Klivans, Pravesh K. Kothari, Raghu Meka:
Efficient Algorithms for Outlier-Robust Regression. COLT 2018: 1420-1430 - [c33]Surbhi Goel, Adam R. Klivans, Raghu Meka:
Learning One Convolutional Layer with Overlapping Patches. ICML 2018: 1778-1786 - [i43]Surbhi Goel, Adam R. Klivans, Raghu Meka:
Learning One Convolutional Layer with Overlapping Patches. CoRR abs/1802.02547 (2018) - [i42]Adam R. Klivans, Pravesh K. Kothari, Raghu Meka:
Efficient Algorithms for Outlier-Robust Regression. CoRR abs/1803.03241 (2018) - [i41]Raghu Meka, Omer Reingold, Avishay Tal:
Pseudorandom Generators for Width-3 Branching Programs. CoRR abs/1806.04256 (2018) - [i40]Nikhil Bansal, Raghu Meka:
On the discrepancy of random low degree set systems. CoRR abs/1810.03374 (2018) - [i39]Ashutosh Kumar, Raghu Meka, Amit Sahai:
Leakage-Resilient Secret Sharing. Electron. Colloquium Comput. Complex. TR18 (2018) - [i38]Raghu Meka, Omer Reingold, Avishay Tal:
Pseudorandom Generators for Width-3 Branching Programs. Electron. Colloquium Comput. Complex. TR18 (2018) - [i37]Ashutosh Kumar, Raghu Meka, Amit Sahai:
Leakage-Resilient Secret Sharing. IACR Cryptol. ePrint Arch. 2018: 1138 (2018) - 2017
- [j12]Clément L. Canonne
, Venkatesan Guruswami, Raghu Meka, Madhu Sudan:
Communication With Imperfectly Shared Randomness. IEEE Trans. Inf. Theory 63(10): 6799-6818 (2017) - [c32]Adam R. Klivans, Raghu Meka:
Learning Graphical Models Using Multiplicative Weights. FOCS 2017: 343-354 - [c31]Raghu Meka:
Explicit Resilient Functions Matching Ajtai-Linial. SODA 2017: 1132-1148 - [c30]Pravesh K. Kothari, Raghu Meka, Prasad Raghavendra:
Approximating rectangles by juntas and weakly-exponential lower bounds for LP relaxations of CSPs. STOC 2017: 590-603 - [i36]Adam R. Klivans, Raghu Meka:
Learning Graphical Models Using Multiplicative Weights. CoRR abs/1706.06274 (2017) - 2016
- [j11]Moritz Hardt, Yuval Ishai, Raghu Meka, Virginia Vassilevska Williams:
Special Section on the Fifty-Fourth Annual IEEE Symposium on Foundations of Computer Science (FOCS 2013). SIAM J. Comput. 45(3): 881 (2016) - [j10]Mika Göös, Shachar Lovett
, Raghu Meka, Thomas Watson, David Zuckerman:
Rectangles Are Nonnegative Juntas. SIAM J. Comput. 45(5): 1835-1869 (2016) - [j9]Raghu Meka, Oanh Nguyen, Van Vu:
Anti-concentration for Polynomials of Independent Random Variables. Theory Comput. 12(1): 1-17 (2016) - [i35]Pravesh Kothari, Raghu Meka, Prasad Raghavendra:
Approximating Rectangles by Juntas and Weakly-Exponential Lower Bounds for LP Relaxations of CSPs. CoRR abs/1610.02704 (2016) - 2015
- [j8]Boaz Barak, Parikshit Gopalan, Johan Håstad
, Raghu Meka, Prasad Raghavendra, David Steurer
:
Making the Long Code Shorter. SIAM J. Comput. 44(5): 1287-1324 (2015) - [j7]Shachar Lovett
, Raghu Meka:
Constructive Discrepancy Minimization by Walking on the Edges. SIAM J. Comput. 44(5): 1573-1582 (2015) - [c29]Parikshit Gopalan, Daniel M. Kane, Raghu Meka:
Pseudorandomness via the Discrete Fourier Transform. FOCS 2015: 903-922 - [c28]Clément Louis Canonne, Venkatesan Guruswami, Raghu Meka, Madhu Sudan:
Communication with Imperfectly Shared Randomness. ITCS 2015: 257-262 - [c27]Raghu Meka, Aaron Potechin
, Avi Wigderson:
Sum-of-squares Lower Bounds for Planted Clique. STOC 2015: 87-96 - [c26]Pravesh K. Kothari, Raghu Meka:
Almost Optimal Pseudorandom Generators for Spherical Caps: Extended Abstract. STOC 2015: 247-256 - [c25]Mika Göös, Shachar Lovett
, Raghu Meka, Thomas Watson, David Zuckerman:
Rectangles Are Nonnegative Juntas. STOC 2015: 257-266 - [i34]Raghu Meka, Aaron Potechin, Avi Wigderson:
Sum-of-squares lower bounds for planted clique. CoRR abs/1503.06447 (2015) - [i33]Parikshit Gopalan, Daniel M. Kane, Raghu Meka:
Pseudorandomness via the discrete Fourier transform. CoRR abs/1506.04350 (2015) - [i32]Raghu Meka:
Explicit resilient functions matching Ajtai-Linial. CoRR abs/1509.00092 (2015) - [i31]Raghu Meka:
Explicit resilient functions matching Ajtai-Linial. Electron. Colloquium Comput. Complex. TR15 (2015) - 2014
- [j6]Prahladh Harsha
, Adam R. Klivans, Raghu Meka:
Bounding the Sensitivity of Polynomial Threshold Functions. Theory Comput. 10: 1-26 (2014) - [c24]Raghu Meka, Omer Reingold, Yuan Zhou:
Deterministic Coupon Collection and Better Strong Dispersers. APPROX-RANDOM 2014: 872-884 - [c23]Elad Hazan, Zohar Shay Karnin, Raghu Meka:
Volumetric Spanners: an Efficient Exploration Basis for Learning. COLT 2014: 408-422 - [c22]Moritz Hardt, Raghu Meka, Prasad Raghavendra, Benjamin Weitz:
Computational Limits for Matrix Completion. COLT 2014: 703-725 - [c21]Raghu Meka, Omer Reingold, Guy N. Rothblum, Ron D. Rothblum:
Fast Pseudorandomness for Independence and Load Balancing - (Extended Abstract). ICALP (1) 2014: 859-870 - [i30]Moritz Hardt, Raghu Meka, Prasad Raghavendra, Benjamin Weitz:
Computational Limits for Matrix Completion. CoRR abs/1402.2331 (2014) - [i29]Clément L. Canonne, Venkatesan Guruswami, Raghu Meka, Madhu Sudan:
Communication with Imperfectly Shared Randomness. CoRR abs/1411.3603 (2014) - [i28]Parikshit Gopalan, Daniel M. Kane, Raghu Meka:
Pseudorandomness for concentration bounds and signed majorities. CoRR abs/1411.4584 (2014) - [i27]Pravesh Kothari, Raghu Meka:
Almost Optimal Pseudorandom Generators for Spherical Caps. CoRR abs/1411.6299 (2014) - [i26]Clément L. Canonne, Venkatesan Guruswami, Raghu Meka, Madhu Sudan:
Communication with Imperfectly Shared Randomness. Electron. Colloquium Comput. Complex. TR14 (2014) - [i25]Mika Göös, Shachar Lovett, Raghu Meka, Thomas Watson, David Zuckerman:
Rectangles Are Nonnegative Juntas. Electron. Colloquium Comput. Complex. TR14 (2014) - 2013
- [j5]Parikshit Gopalan, Raghu Meka, Omer Reingold:
DNF sparsification and a faster deterministic counting algorithm. Comput. Complex. 22(2): 275-310 (2013) - [j4]Parikshit Gopalan, Raghu Meka, Omer Reingold, David Zuckerman:
Pseudorandom Generators for Combinatorial Shapes. SIAM J. Comput. 42(3): 1051-1076 (2013) - [j3]Raghu Meka, David Zuckerman:
Pseudorandom Generators for Polynomial Threshold Functions. SIAM J. Comput. 42(3): 1275-1301 (2013) - [c20]Daniel M. Kane, Adam R. Klivans, Raghu Meka:
Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching. COLT 2013: 522-545 - [c19]Daniel M. Kane, Raghu Meka:
A PRG for lipschitz functions of polynomials with applications to sparsest cut. STOC 2013: 1-10 - [i24]Adam R. Klivans, Raghu Meka:
Moment-Matching Polynomials. CoRR abs/1301.0820 (2013) - [i23]Elad Hazan, Zohar Shay Karnin, Raghu Meka:
Volumetric Spanners and their Applications to Machine Learning. CoRR abs/1312.6214 (2013) - [i22]Adam R. Klivans, Raghu Meka:
Moment-Matching Polynomials. Electron. Colloquium Comput. Complex. TR13 (2013) - [i21]Raghu Meka, Avi Wigderson:
Association schemes, non-commutative polynomial concentration, and sum-of-squares lower bounds for planted clique. Electron. Colloquium Comput. Complex. TR13 (2013) - 2012
- [j2]Prahladh Harsha
, Adam R. Klivans, Raghu Meka:
An invariance principle for polytopes. J. ACM 59(6): 29:1-29:25 (2012) - [c18]Parikshit Gopalan, Raghu Meka, Omer Reingold:
DNF Sparsification and a Faster Deterministic Counting Algorithm. CCC 2012: 126-135 - [c17]Shachar Lovett
, Raghu Meka:
Constructive Discrepancy Minimization by Walking on the Edges. FOCS 2012: 61-67 - [c16]Russell Impagliazzo
, Raghu Meka, David Zuckerman:
Pseudorandomness from Shrinkage. FOCS 2012: 111-119 - [c15]Parikshit Gopalan, Raghu Meka, Omer Reingold, Luca Trevisan
, Salil P. Vadhan:
Better Pseudorandom Generators from Milder Pseudorandom Restrictions. FOCS 2012: 120-129 - [c14]Raghu Meka:
A PTAS for Computing the Supremum of Gaussian Processes. FOCS 2012: 217-222 - [c13]Boaz Barak, Parikshit Gopalan, Johan Håstad
, Raghu Meka, Prasad Raghavendra, David Steurer
:
Making the Long Code Shorter. FOCS 2012: 370-379 - [c12]Parikshit Gopalan, Adam R. Klivans, Raghu Meka:
Learning Functions of Halfspaces using Prefix Covers. COLT 2012: 15.1-15.10 - [i20]Raghu Meka:
A PTAS for Computing the Supremum of Gaussian Processes. CoRR abs/1202.4970 (2012) - [i19]Shachar Lovett, Raghu Meka:
Constructive Discrepancy Minimization by Walking on The Edges. CoRR abs/1203.5747 (2012) - [i18]Parikshit Gopalan, Raghu Meka, Omer Reingold:
DNF Sparsification and a Faster Deterministic Counting Algorithm. CoRR abs/1205.3534 (2012) - [i17]Parikshit Gopalan, Raghu Meka, Omer Reingold, Luca Trevisan, Salil P. Vadhan:
Better Pseudorandom Generators from Milder Pseudorandom Restrictions. CoRR abs/1210.0049 (2012) - [i16]Daniel M. Kane, Raghu Meka:
A PRG for Lipschitz Functions of Polynomials with Applications to Sparsest Cut. CoRR abs/1211.1109 (2012) - [i15]Parikshit Gopalan, Raghu Meka, Omer Reingold:
DNF Sparsification and a Faster Deterministic Counting. Electron. Colloquium Comput. Complex. TR12 (2012) - [i14]Parikshit Gopalan, Raghu Meka, Omer Reingold, Luca Trevisan, Salil P. Vadhan:
Better pseudorandom generators from milder pseudorandom restrictions. Electron. Colloquium Comput. Complex. TR12 (2012) - [i13]Russell Impagliazzo, Raghu Meka, David Zuckerman:
Pseudorandomness from Shrinkage. Electron. Colloquium Comput. Complex. TR12 (2012) - 2011
- [c11]Daniel Kane, Raghu Meka, Jelani Nelson:
Almost Optimal Explicit Johnson-Lindenstrauss Families. APPROX-RANDOM 2011: 628-639 - [c10]Parikshit Gopalan, Adam R. Klivans, Raghu Meka, Daniel Stefankovic
, Santosh S. Vempala, Eric Vigoda:
An FPTAS for #Knapsack and Related Counting Problems. FOCS 2011: 817-826 - [c9]Parikshit Gopalan, Raghu Meka, Omer Reingold, David Zuckerman:
Pseudorandom generators for combinatorial shapes. STOC 2011: 253-262 - [i12]Boaz Barak, Parikshit Gopalan, Johan Håstad, Raghu Meka, Prasad Raghavendra, David Steurer:
Making the long code shorter, with applications to the Unique Games Conjecture. CoRR abs/1111.0405 (2011) - [i11]Boaz Barak, Parikshit Gopalan, Johan Håstad, Raghu Meka, Prasad Raghavendra, David Steurer:
Making the long code shorter, with applications to the Unique Games Conjecture. Electron. Colloquium Comput. Complex. TR11 (2011) - 2010
- [c8]Prateek Jain, Raghu Meka, Inderjit S. Dhillon:
Guaranteed Rank Minimization via Singular Value Projection. NIPS 2010: 937-945 - [c7]Raghu Meka, David Zuckerman:
Pseudorandom generators for polynomial threshold functions. STOC 2010: 427-436 - [c6]Ilias Diakonikolas, Prahladh Harsha
, Adam R. Klivans, Raghu Meka, Prasad Raghavendra, Rocco A. Servedio, Li-Yang Tan:
Bounding the average sensitivity and noise sensitivity of polynomial threshold functions. STOC 2010: 533-542 - [c5]Prahladh Harsha
, Adam R. Klivans, Raghu Meka:
An invariance principle for polytopes. STOC 2010: 543-552 - [i10]Parikshit Gopalan, Adam R. Klivans, Raghu Meka:
Polynomial-Time Approximation Schemes for Knapsack and Related Counting Problems using Branching Programs. CoRR abs/1008.3187 (2010) - [i9]Raghu Meka:
Almost Optimal Explicit Johnson-Lindenstrauss Transformations. CoRR abs/1011.6397 (2010) - [i8]Parikshit Gopalan, Adam R. Klivans, Raghu Meka:
Polynomial-Time Approximation Schemes for Knapsack and Related Counting Problems using Branching Programs. Electron. Colloquium Comput. Complex. TR10 (2010) - [i7]Parikshit Gopalan, Raghu Meka, Omer Reingold, David Zuckerman:
Pseudorandom Generators for Combinatorial Shapes. Electron. Colloquium Comput. Complex. TR10 (2010) - [i6]Daniel Kane, Raghu Meka, Jelani Nelson:
Almost Optimal Explicit Johnson-Lindenstrauss Transformations. Electron. Colloquium Comput. Complex. TR10 (2010)
2000 – 2009
- 2009
- [c4]Raghu Meka, David Zuckerman:
Small-Bias Spaces for Group Products. APPROX-RANDOM 2009: 658-672 - [c3]Raghu Meka, Prateek Jain, Inderjit S. Dhillon:
Matrix Completion from Power-Law Distributed Samples. NIPS 2009: 1258-1266 - [i5]Prahladh Harsha, Adam R. Klivans, Raghu Meka:
Bounding the Sensitivity of Polynomial Threshold Functions. CoRR abs/0909.5175 (2009) - [i4]Raghu Meka, Prateek Jain, Inderjit S. Dhillon:
Guaranteed Rank Minimization via Singular Value Projection. CoRR abs/0909.5457 (2009) - [i3]Raghu Meka, David Zuckerman:
Pseudorandom Generators for Polynomial Threshold Functions. CoRR abs/0910.4122 (2009) - [i2]Prahladh Harsha, Adam R. Klivans, Raghu Meka:
An Invariance Principle for Polytopes. CoRR abs/0912.4884 (2009) - [i1]Prahladh Harsha, Adam R. Klivans, Raghu Meka:
An Invariance Principle for Polytopes. Electron. Colloquium Comput. Complex. TR09 (2009) - 2008
- [j1]Prateek Jain, Raghu Meka, Inderjit S. Dhillon:
Simultaneous Unsupervised Learning of Disparate Clusterings. Stat. Anal. Data Min. 1(3): 195-210 (2008) - [c2]Raghu Meka, Prateek Jain, Constantine Caramanis
, Inderjit S. Dhillon:
Rank minimization via online learning. ICML 2008: 656-663 - [c1]Prateek Jain, Raghu Meka, Inderjit S. Dhillon:
Simultaneous Unsupervised Learning of Disparate Clusterings. SDM 2008: 858-869
Coauthor Index
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
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