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ORCIDShachar Lovett
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- affiliation: University of California at San Diego, La Jolla, CA, USA
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2020 – today
- 2024
[j47]Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan:
Realizable Learning is All You Need. TheoretiCS 3 (2024)- [c87]Hamed Hatami, Kaave Hosseini, Shachar Lovett, Anthony Ostuni:
Refuting Approaches to the Log-Rank Conjecture for XOR Functions. ICALP 2024: 82:1-82:11 - [c86]Amir Abboud
, Nick Fischer, Zander Kelley, Shachar Lovett, Raghu Meka:
New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms. STOC 2024: 935-943 - [c85]Zander Kelley, Shachar Lovett, Raghu Meka:
Explicit Separations between Randomized and Deterministic Number-on-Forehead Communication. STOC 2024: 1299-1310 - [i147]Michael Jaber, Shachar Lovett, Anthony Ostuni:
Corners in Quasirandom Groups via Sparse Mixing. CoRR abs/2411.02702 (2024) - [i146]Michael Jaber, Shachar Lovett, Anthony Ostuni:
Corners in Quasirandom Groups via Sparse Mixing. Electron. Colloquium Comput. Complex. TR24 (2024) - 2023
- [j46]Abhishek Bhowmick, Shachar Lovett:
Bias vs Structure of Polynomials in Large Fields, and Applications in Information Theory. IEEE Trans. Inf. Theory 69(2): 963-977 (2023) - [c84]Sihan Liu, Gaurav Mahajan, Daniel Kane, Shachar Lovett, Gellért Weisz, Csaba Szepesvári:
Exponential Hardness of Reinforcement Learning with Linear Function Approximation. COLT 2023: 1588-1617 - [c83]Shachar Lovett, Jiapeng Zhang:
Streaming Lower Bounds and Asymmetric Set-Disjointness. FOCS 2023: 871-882 - [c82]Shachar Lovett, Jiapeng Zhang:
Fractional Certificates for Bounded Functions. ITCS 2023: 84:1-84:13 - [c81]Daniel Beaglehole, Max Hopkins, Daniel Kane, Sihan Liu, Shachar Lovett:
Sampling Equilibria: Fast No-Regret Learning in Structured Games. SODA 2023: 3817-3855 - [i145]Shachar Lovett, Jiapeng Zhang:
Streaming Lower Bounds and Asymmetric Set-Disjointness. CoRR abs/2301.05658 (2023) - [i144]Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan:
Do PAC-Learners Learn the Marginal Distribution? CoRR abs/2302.06285 (2023) - [i143]Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan, Csaba Szepesvári, Gellért Weisz:
Exponential Hardness of Reinforcement Learning with Linear Function Approximation. CoRR abs/2302.12940 (2023) - [i142]Zander Kelley, Shachar Lovett, Raghu Meka:
Explicit separations between randomized and deterministic Number-on-Forehead communication. CoRR abs/2308.12451 (2023) - [i141]Amir Abboud, Nick Fischer, Zander Kelley, Shachar Lovett, Raghu Meka:
New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms. CoRR abs/2311.09095 (2023) - [i140]Hamed Hatami, Kaave Hosseini, Shachar Lovett, Anthony Ostuni:
Refuting approaches to the log-rank conjecture for XOR functions. CoRR abs/2312.09400 (2023) - [i139]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) - [i138]Hamed Hatami, Kaave Hosseini, Shachar Lovett, Anthony Ostuni:
Refuting approaches to the log-rank conjecture for XOR functions. Electron. Colloquium Comput. Complex. TR23 (2023) - [i137]Zander Kelley, Shachar Lovett, Raghu Meka:
Explicit separations between randomized and deterministic Number-on-Forehead communication. Electron. Colloquium Comput. Complex. TR23 (2023) - [i136]Shachar Lovett, Jiapeng Zhang:
Streaming Lower Bounds and Asymmetric Set-Disjointness. Electron. Colloquium Comput. Complex. TR23 (2023) - 2022
- [j45]Xin Li, Shachar Lovett, Jiapeng Zhang:
Sunflowers and Robust Sunflowers from Randomness Extractors. Adv. Math. Commun. 18: 1-18 (2022) - [j44]Kaave Hosseini, Hamed Hatami, Shachar Lovett:
Sign-Rank vs. Discrepancy. Adv. Math. Commun. 18: 1-22 (2022) - [c80]Jason Gaitonde, Max Hopkins, Tali Kaufman, Shachar Lovett, Ruizhe Zhang:
Eigenstripping, Spectral Decay, and Edge-Expansion on Posets. APPROX/RANDOM 2022: 16:1-16:24 - [c79]Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan:
Computational-Statistical Gap in Reinforcement Learning. COLT 2022: 1282-1302 - [c78]Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan:
Realizable Learning is All You Need. COLT 2022: 3015-3069 - [c77]Shachar Lovett, Raghu Meka, Ian Mertz, Toniann Pitassi, Jiapeng Zhang:
Lifting with Sunflowers. ITCS 2022: 104:1-104:24 - [c76]Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett:
High Dimensional Expanders: Eigenstripping, Pseudorandomness, and Unique Games. SODA 2022: 1069-1128 - [c75]Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett:
Hypercontractivity on high dimensional expanders. STOC 2022: 185-194 - [e1]Shachar Lovett:
37th Computational Complexity Conference, CCC 2022, July 20-23, 2022, Philadelphia, PA, USA. LIPIcs 234, Schloss Dagstuhl - Leibniz-Zentrum für Informatik 2022, ISBN 978-3-95977-241-9 [contents] - [i135]Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan:
Computational-Statistical Gaps in Reinforcement Learning. CoRR abs/2202.05444 (2022) - [i134]Jason Gaitonde, Max Hopkins, Tali Kaufman, Shachar Lovett, Ruizhe Zhang:
Eigenstripping, Spectral Decay, and Edge-Expansion on Posets. CoRR abs/2205.00644 (2022) - [i133]Shachar Lovett, Jiapeng Zhang:
Fractional certificates for bounded functions. Electron. Colloquium Comput. Complex. TR22 (2022) - 2021
- [j43]Shachar Lovett, Kewen Wu, Jiapeng Zhang:
Decision List Compression by Mild Random Restrictions. J. ACM 68(6): 45:1-45:17 (2021) - [j42]Shachar Lovett:
Sparse MDS Matrices over Small Fields: A Proof of the GM-MDS Conjecture. SIAM J. Comput. 50(4): 1248-1262 (2021) - [j41]Alexander Knop, Shachar Lovett, Sam McGuire, Weiqiang Yuan:
Guest Column: Models of computation between decision trees and communication. SIGACT News 52(2): 46-70 (2021) - [c74]Sankeerth Rao Karingula, Shachar Lovett:
Singularity of Random Integer Matrices with Large Entries. APPROX-RANDOM 2021: 33:1-33:16 - [c73]Eshan Chattopadhyay, Jason Gaitonde, Chin Ho Lee, Shachar Lovett, Abhishek Shetty:
Fractional Pseudorandom Generators from Any Fourier Level. CCC 2021: 10:1-10:24 - [c72]Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz:
Bounded Memory Active Learning through Enriched Queries. COLT 2021: 2358-2387 - [c71]Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang:
Bilinear Classes: A Structural Framework for Provable Generalization in RL. ICML 2021: 2826-2836 - [c70]Alexander Knop, Shachar Lovett, Sam McGuire, Weiqiang Yuan:
Log-rank and lifting for AND-functions. STOC 2021: 197-208 - [i132]Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz:
Bounded Memory Active Learning through Enriched Queries. CoRR abs/2102.05047 (2021) - [i131]Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang:
Bilinear Classes: A Structural Framework for Provable Generalization in RL. CoRR abs/2103.10897 (2021) - [i130]Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan:
Realizable Learning is All You Need. CoRR abs/2111.04746 (2021) - [i129]Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett:
Hypercontractivity on High Dimensional Expanders: a Local-to-Global Approach for Higher Moments. CoRR abs/2111.09444 (2021) - [i128]Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett:
Hypercontractivity on High Dimensional Expanders: a Local-to-Global Approach for Higher Moments. Electron. Colloquium Comput. Complex. TR21 (2021) - 2020
- [j40]Shachar Lovett, Sankeerth Rao, Alexander Vardy:
Probabilistic existence of large sets of designs. J. Comb. Theory A 176: 105286 (2020) - [c69]Hamed Hatami, Kaave Hosseini, Shachar Lovett:
Sign Rank vs Discrepancy. CCC 2020: 18:1-18:14 - [c68]Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan:
Noise-tolerant, Reliable Active Classification with Comparison Queries. COLT 2020: 1957-2006 - [c67]Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan:
Point Location and Active Learning: Learning Halfspaces Almost Optimally. FOCS 2020: 1034-1044 - [c66]Alon Gonen, Shachar Lovett, Michal Moshkovitz:
Towards a Combinatorial Characterization of Bounded-Memory Learning. NeurIPS 2020 - [c65]Max Hopkins, Daniel Kane, Shachar Lovett:
The Power of Comparisons for Actively Learning Linear Classifiers. NeurIPS 2020 - [c64]Eshan Chattopadhyay, Pooya Hatami, Kaave Hosseini, Shachar Lovett, David Zuckerman:
XOR lemmas for resilient functions against polynomials. STOC 2020: 234-246 - [c63]Shachar Lovett, Kewen Wu, Jiapeng Zhang:
Decision list compression by mild random restrictions. STOC 2020: 247-254 - [c62]Ryan Alweiss, Shachar Lovett, Kewen Wu, Jiapeng Zhang:
Improved bounds for the sunflower lemma. STOC 2020: 624-630 - [i127]Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan:
Noise-tolerant, Reliable Active Classification with Comparison Queries. CoRR abs/2001.05497 (2020) - [i126]Alon Gonen, Shachar Lovett, Michal Moshkovitz:
Towards a combinatorial characterization of bounded memory learning. CoRR abs/2002.03123 (2020) - [i125]Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan:
Point Location and Active Learning: Learning Halfspaces Almost Optimally. CoRR abs/2004.11380 (2020) - [i124]Eshan Chattopadhyay, Jason Gaitonde, Chin Ho Lee, Shachar Lovett, Abhishek Shetty:
Fractional Pseudorandom Generators from Any Fourier Level. CoRR abs/2008.01316 (2020) - [i123]Alexander Knop, Shachar Lovett, Sam McGuire, Weiqiang Yuan:
Log-rank and lifting for AND-functions. CoRR abs/2010.08994 (2020) - [i122]Sankeerth Rao Karingula, Shachar Lovett:
Codes over integers, and the singularity of random matrices with large entries. CoRR abs/2010.12081 (2020) - [i121]Max Hopkins, Tali Kaufman, Shachar Lovett:
High Dimensional Expanders: Random Walks, Pseudorandomness, and Unique Games. CoRR abs/2011.04658 (2020) - [i120]Max Hopkins, Tali Kaufman, Shachar Lovett:
High Dimensional Expanders: Random Walks, Pseudorandomness, and Unique Games. Electron. Colloquium Comput. Complex. TR20 (2020) - [i119]Sankeerth Rao Karingula, Shachar Lovett:
Codes over integers, and the singularity of random matrices with large entries. Electron. Colloquium Comput. Complex. TR20 (2020) - [i118]Alexander Knop, Shachar Lovett, Sam McGuire, Weiqiang Yuan:
Log-rank and lifting for AND-functions. Electron. Colloquium Comput. Complex. TR20 (2020) - [i117]Shachar Lovett, Raghu Meka, Jiapeng Zhang:
Improved lifting theorems via robust sunflowers. Electron. Colloquium Comput. Complex. TR20 (2020)
2010 – 2019
- 2019
- [j39]Hamed Hatami, Pooya Hatami, Shachar Lovett:
Higher-order Fourier Analysis and Applications. Found. Trends Theor. Comput. Sci. 13(4): 247-448 (2019) - [j38]Daniel M. Kane, Shachar Lovett, Shay Moran:
Near-optimal Linear Decision Trees for k-SUM and Related Problems. J. ACM 66(3): 16:1-16:18 (2019) - [j37]Esther Ezra, Shachar Lovett:
On the Beck-Fiala conjecture for random set systems. Random Struct. Algorithms 54(4): 665-675 (2019) - [j36]Daniel Kane, Shachar Lovett, Sankeerth Rao:
The Independence Number of the Birkhoff Polytope Graph, and Applications to Maximally Recoverable Codes. SIAM J. Comput. 48(4): 1425-1435 (2019) - [j35]Nikhil Bansal, Daniel Dadush, Shashwat Garg, Shachar Lovett:
The Gram-Schmidt Walk: A Cure for the Banaszczyk Blues. Theory Comput. 15: 1-27 (2019) - [j34]Eshan Chattopadhyay, Pooya Hatami, Kaave Hosseini, Shachar Lovett:
Pseudorandom Generators from Polarizing Random Walks. Theory Comput. 15: 1-26 (2019) - [j33]Daniel Dadush, Shashwat Garg, Shachar Lovett, Aleksandar Nikolov:
Towards a Constructive Version of Banaszczyk's Vector Balancing Theorem. Theory Comput. 15: 1-58 (2019) - [c61]Shachar Lovett, Noam Solomon, Jiapeng Zhang:
From DNF Compression to Sunflower Theorems via Regularity. CCC 2019: 5:1-5:14 - [c60]Kaave Hosseini, Shachar Lovett, Grigory Yaroslavtsev:
Optimality of Linear Sketching Under Modular Updates. CCC 2019: 13:1-13:17 - [c59]Arkadev Chattopadhyay, Shachar Lovett, Marc Vinyals:
Equality Alone Does not Simulate Randomness. CCC 2019: 14:1-14:11 - [c58]Abhishek Bhrushundi, Kaave Hosseini, Shachar Lovett, Sankeerth Rao:
Torus Polynomials: An Algebraic Approach to ACC Lower Bounds. ITCS 2019: 13:1-13:16 - [c57]Eshan Chattopadhyay, Pooya Hatami, Shachar Lovett, Avishay Tal:
Pseudorandom Generators from the Second Fourier Level and Applications to AC0 with Parity Gates. ITCS 2019: 22:1-22:15 - [c56]Shachar Lovett, Jiapeng Zhang:
DNF sparsification beyond sunflowers. STOC 2019: 454-460 - [i116]Shachar Lovett, Noam Solomon, Jiapeng Zhang:
From DNF compression to sunflower theorems via regularity. CoRR abs/1903.00580 (2019) - [i115]Max Hopkins, Daniel M. Kane, Shachar Lovett:
The Power of Comparisons for Actively Learning Linear Classifiers. CoRR abs/1907.03816 (2019) - [i114]Ryan Alweiss, Shachar Lovett, Kewen Wu, Jiapeng Zhang:
Improved bounds for the sunflower lemma. CoRR abs/1908.08483 (2019) - [i113]Shachar Lovett, Kewen Wu, Jiapeng Zhang:
Decision list compression by mild random restrictions. CoRR abs/1909.10658 (2019) - [i112]Ryan Alweiss, Shachar Lovett, Kewen Wu, Jiapeng Zhang:
Improved bounds for the sunflower lemma. Electron. Colloquium Comput. Complex. TR19 (2019) - [i111]Eshan Chattopadhyay, Pooya Hatami, Kaave Hosseini, Shachar Lovett, David Zuckerman:
XOR Lemmas for Resilient Functions Against Polynomials. Electron. Colloquium Comput. Complex. TR19 (2019) - [i110]Hamed Hatami, Kaave Hosseini, Shachar Lovett:
Sign rank vs Discrepancy. Electron. Colloquium Comput. Complex. TR19 (2019) - [i109]Shachar Lovett, Noam Solomon, Jiapeng Zhang:
From DNF compression to sunflower theorems via regularity. Electron. Colloquium Comput. Complex. TR19 (2019) - [i108]Shachar Lovett, Kewen Wu, Jiapeng Zhang:
Decision list compression by mild random restrictions. Electron. Colloquium Comput. Complex. TR19 (2019) - 2018
- [j32]Benny Applebaum, Shachar Lovett:
Algebraic Attacks against Random Local Functions and Their Countermeasures. SIAM J. Comput. 47(1): 52-79 (2018) - [j31]Hamed Hatami, Kaave Hosseini, Shachar Lovett:
Structure of Protocols for XOR Functions. SIAM J. Comput. 47(1): 208-217 (2018) - [j30]Divesh Aggarwal, Yevgeniy Dodis, Shachar Lovett:
Non-Malleable Codes from Additive Combinatorics. SIAM J. Comput. 47(2): 524-546 (2018) - [j29]Abhishek Bhowmick, Shachar Lovett:
The List Decoding Radius for Reed-Muller Codes Over Small Fields. IEEE Trans. Inf. Theory 64(6): 4382-4391 (2018) - [j28]Shachar Lovett, Ryan O'Donnell:
Special Issue: CCC 2017: Guest Editor's Foreword. Theory Comput. 14(1): 1-2 (2018) - [c55]Xin Li, Shachar Lovett, Jiapeng Zhang:
Sunflowers and Quasi-Sunflowers from Randomness Extractors. APPROX-RANDOM 2018: 51:1-51:13 - [c54]Eshan Chattopadhyay, Pooya Hatami, Kaave Hosseini, Shachar Lovett:
Pseudorandom Generators from Polarizing Random Walks. CCC 2018: 1:1-1:21 - [c53]Marco L. Carmosino, Russell Impagliazzo, Shachar Lovett, Ivan Mihajlin:
Hardness Amplification for Non-Commutative Arithmetic Circuits. CCC 2018: 12:1-12:16 - [c52]Shachar Lovett:
MDS Matrices over Small Fields: A Proof of the GM-MDS Conjecture. FOCS 2018: 194-199 - [c51]Daniel M. Kane, Shachar Lovett, Shay Moran:
Generalized Comparison Trees for Point-Location Problems. ICALP 2018: 82:1-82:13 - [c50]Shachar Lovett, Sankeerth Rao, Alexander Vardy:
Probabilistic Existence of Large Sets of Designs. SODA 2018: 1545-1556 - [c49]Shachar Lovett, Avishay Tal, Jiapeng Zhang:
The Robust Sensitivity of Boolean Functions. SODA 2018: 1822-1833 - [c48]Daniel M. Kane, Shachar Lovett, Shay Moran:
Near-optimal linear decision trees for k-SUM and related problems. STOC 2018: 554-563 - [c47]Nikhil Bansal, Daniel Dadush, Shashwat Garg, Shachar Lovett:
The gram-schmidt walk: a cure for the Banaszczyk blues. STOC 2018: 587-597 - [i107]Shachar Lovett:
MDS matrices over small fields: A proof of the GM-MDS conjecture. CoRR abs/1803.02523 (2018) - [i106]Abhishek Bhrushundi, Kaave Hosseini, Shachar Lovett, Sankeerth Rao:
Torus polynomials: an algebraic approach to ACC lower bounds. CoRR abs/1804.08176 (2018) - [i105]Daniel M. Kane, Shachar Lovett, Shay Moran:
Generalized comparison trees for point-location problems. CoRR abs/1804.08237 (2018) - [i104]Kaave Hosseini, Shachar Lovett, Grigory Yaroslavtsev:
Optimality of Linear Sketching under Modular Updates. CoRR abs/1809.09063 (2018) - [i103]Abhishek Bhrushundi, Kaave Hosseini, Shachar Lovett, Sankeerth Rao:
Torus polynomials: an algebraic approach to ACC lower bounds. Electron. Colloquium Comput. Complex. TR18 (2018) - [i102]Marco Carmosino, Russell Impagliazzo, Shachar Lovett, Ivan Mihajlin:
Hardness Amplification for Non-Commutative Arithmetic Circuits. Electron. Colloquium Comput. Complex. TR18 (2018) - [i101]Eshan Chattopadhyay, Pooya Hatami, Kaave Hosseini, Shachar Lovett:
Pseudorandom Generators from Polarizing Random Walks. Electron. Colloquium Comput. Complex. TR18 (2018) - [i100]Eshan Chattopadhyay, Pooya Hatami, Shachar Lovett, Avishay Tal:
Pseudorandom generators from the second Fourier level and applications to AC0 with parity gates. Electron. Colloquium Comput. Complex. TR18 (2018) - [i99]Arkadev Chattopadhyay, Shachar Lovett, Marc Vinyals:
Equality Alone Does Not Simulate Randomness. Electron. Colloquium Comput. Complex. TR18 (2018) - [i98]Kaave Hosseini, Shachar Lovett:
A bilinear Bogolyubov-Ruzsa lemma with poly-logarithmic bounds. Electron. Colloquium Comput. Complex. TR18 (2018) - [i97]Kaave Hosseini, Shachar Lovett, Grigory Yaroslavtsev:
Optimality of Linear Sketching under Modular Updates. Electron. Colloquium Comput. Complex. TR18 (2018) - [i96]Daniel M. Kane, Shachar Lovett, Shay Moran:
Generalized comparison trees for point-location problems. Electron. Colloquium Comput. Complex. TR18 (2018) - [i95]Xin Li, Shachar Lovett, Jiapeng Zhang:
Sunflowers and Quasi-sunflowers from Randomness Extractors. Electron. Colloquium Comput. Complex. TR18 (2018) - [i94]Shachar Lovett:
A proof of the GM-MDS conjecture. Electron. Colloquium Comput. Complex. TR18 (2018) - [i93]Shachar Lovett, Jiapeng Zhang:
DNF sparsification beyond sunflowers. Electron. Colloquium Comput. Complex. TR18 (2018) - 2017
- [j27]Kaave Hosseini, Shachar Lovett:
On the structure of the spectrum of small sets. J. Comb. Theory A 148: 1-14 (2017) - [j26]Shachar Lovett:
Additive Combinatorics and its Applications in Theoretical Computer Science. Theory Comput. 8: 1-55 (2017) - [c46]Shachar Lovett, Jiapeng Zhang:
Noisy Population Recovery from Unknown Noise. COLT 2017: 1417-1431 - [c45]Daniel Kane, Shachar Lovett, Sankeerth Rao:
The Independence Number of the Birkhoff Polytope Graph, and Applications to Maximally Recoverable Codes. FOCS 2017: 252-259 - [c44]Daniel M. Kane, Shachar Lovett, Shay Moran, Jiapeng Zhang:
Active Classification with Comparison Queries. FOCS 2017: 355-366 - [c43]Shachar Lovett, Jiapeng Zhang:
On the Impossibility of Entropy Reversal, and Its Application to Zero-Knowledge Proofs. TCC (1) 2017: 31-55 - [i92]Daniel M. Kane, Shachar Lovett, Sankeerth Rao:
Labeling the complete bipartite graph with no zero cycles. CoRR abs/1702.05773 (2017) - [i91]Daniel M. Kane, Shachar Lovett, Shay Moran, Jiapeng Zhang:
Active classification with comparison queries. CoRR abs/1704.03564 (2017) - [i90]Daniel M. Kane, Shachar Lovett, Shay Moran:
Near-optimal linear decision trees for k-SUM and related problems. CoRR abs/1705.01720 (2017) - [i89]Nikhil Bansal, Daniel Dadush, Shashwat Garg, Shachar Lovett:
The Gram-Schmidt Walk: A Cure for the Banaszczyk Blues. CoRR abs/1708.01079 (2017) - [i88]Daniel M. Kane, Shachar Lovett, Shay Moran:
Near-optimal linear decision trees for k-SUM and related problems. Electron. Colloquium Comput. Complex. TR17 (2017) - [i87]