Tselil Schramm

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 53

Top Topics

Spectral Clustering

Tensor Decomposition

High Dimensional

Top Venues

Publications

Misha Ivkov, Tselil Schramm
Semidefinite Programs Simulate Approximate Message Passing Robustly. STOC (2024)
Siqi Liu, Sidhanth Mohanty, Tselil Schramm, Elizabeth Yang
Local and Global Expansion in Random Geometric Graphs. STOC (2023)
Misha Ivkov, Tselil Schramm
Semidefinite programs simulate approximate message passing robustly. CoRR (2023)
Shuangping Li, Tselil Schramm
Spectral clustering in the Gaussian mixture block model. CoRR (2023)
Siqi Liu, Sidhanth Mohanty, Tselil Schramm, Elizabeth Yang
Local and global expansion in random geometric graphs. CoRR (2022)
Afonso S. Bandeira, Ahmed El Alaoui, Samuel B. Hopkins, Tselil Schramm, Alexander S. Wein, Ilias Zadik
The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics. NeurIPS (2022)
Siqi Liu, Sidhanth Mohanty, Tselil Schramm, Elizabeth Yang
Testing thresholds for high-dimensional sparse random geometric graphs. STOC (2022)
Amulya Musipatla, Ryan O'Donnell, Tselil Schramm, Xinyu Wu
The SDP Value of Random 2CSPs. ICALP (2022)
Afonso S. Bandeira, Ahmed El Alaoui, Samuel B. Hopkins, Tselil Schramm, Alexander S. Wein, Ilias Zadik
The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics. CoRR (2022)
Samuel B. Hopkins, Tselil Schramm, Jonathan Shi
A Robust Spectral Algorithm for Overcomplete Tensor Decomposition. CoRR (2022)
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
Robust Regression Revisited: Acceleration and Improved Estimation Rates. CoRR (2021)
Ronen Eldan, Dan Mikulincer, Tselil Schramm
Non-asymptotic approximations of neural networks by Gaussian processes. CoRR (2021)
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
Robust Regression Revisited: Acceleration and Improved Estimation Rates. NeurIPS (2021)
Matthew S. Brennan, Guy Bresler, Samuel B. Hopkins, Jerry Li, Tselil Schramm
Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent. COLT (2021)
Mitali Bafna, Boaz Barak, Pravesh K. Kothari, Tselil Schramm, David Steurer
Playing unique games on certified small-set expanders. STOC (2021)
Ronen Eldan, Dan Mikulincer, Tselil Schramm
Non-asymptotic approximations of neural networks by Gaussian processes. COLT (2021)
Amulya Musipatla, Ryan O'Donnell, Tselil Schramm, Xinyu Wu
The SDP value of random 2CSPs. CoRR (2021)
Siqi Liu, Sidhanth Mohanty, Tselil Schramm, Elizabeth Yang
Testing thresholds for high-dimensional sparse random geometric graphs. CoRR (2021)
Pasin Manurangsi, Aviad Rubinstein, Tselil Schramm
The Strongish Planted Clique Hypothesis and Its Consequences. ITCS (2021)
Ryan O'Donnell, Tselil Schramm
Sherali-Adams Strikes Back. Theory Comput. 17 (2021)
Tselil Schramm, Alexander S. Wein
Computational Barriers to Estimation from Low-Degree Polynomials. CoRR (2020)
Samuel B. Hopkins, Tselil Schramm, Luca Trevisan
Subexponential LPs Approximate Max-Cut. FOCS (2020)
Matthew S. Brennan, Guy Bresler, Samuel B. Hopkins, Jerry Li, Tselil Schramm
Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent. CoRR (2020)
Pasin Manurangsi, Aviad Rubinstein, Tselil Schramm
The Strongish Planted Clique Hypothesis and Its Consequences. CoRR (2020)
Mitali Bafna, Boaz Barak, Pravesh Kothari, Tselil Schramm, David Steurer
Playing Unique Games on Certified Small-Set Expanders. CoRR (2020)
Yash Deshpande, Andrea Montanari, Ryan O'Donnell, Tselil Schramm, Subhabrata Sen
The threshold for SDP-refutation of random regular NAE-3SAT. SODA (2019)
Boaz Barak, Chi-Ning Chou, Zhixian Lei, Tselil Schramm, Yueqi Sheng
(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs. NeurIPS (2019)
Ryan O'Donnell, Tselil Schramm
Sherali - Adams Strikes Back. Computational Complexity Conference (2019)
Samuel B. Hopkins, Tselil Schramm, Jonathan Shi
A Robust Spectral Algorithm for Overcomplete Tensor Decomposition. COLT (2019)
Pravesh K. Kothari, Ryan O'Donnell, Tselil Schramm
SOS Lower Bounds with Hard Constraints: Think Global, Act Local. ITCS (2019)
Samuel B. Hopkins, Tselil Schramm, Luca Trevisan
Subexponential LPs Approximate Max-Cut. CoRR (2019)
Boaz Barak, Chi-Ning Chou, Zhixian Lei, Tselil Schramm, Yueqi Sheng
(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs. CoRR (2018)
Prasad Raghavendra, Tselil Schramm, David Steurer
High-dimensional estimation via sum-of-squares proofs. CoRR (2018)
Yash Deshpande, Andrea Montanari, Ryan O'Donnell, Tselil Schramm, Subhabrata Sen
The threshold for SDP-refutation of random regular NAE-3SAT. CoRR (2018)
Pravesh Kothari, Ryan O'Donnell, Tselil Schramm
SOS lower bounds with hard constraints: think global, act local. CoRR (2018)
Ryan O'Donnell, Tselil Schramm
Sherali-Adams Strikes Back. CoRR (2018)
Aviad Rubinstein, Tselil Schramm, S. Matthew Weinberg
Computing Exact Minimum Cuts Without Knowing the Graph. ITCS (2018)
Samuel B. Hopkins, Pravesh Kothari, Aaron Henry Potechin, Prasad Raghavendra, Tselil Schramm
On the Integrality Gap of Degree-4 Sum of Squares for Planted Clique. ACM Trans. Algorithms 14 (3) (2018)
Aviad Rubinstein, Tselil Schramm, S. Matthew Weinberg
Computing exact minimum cuts without knowing the graph. CoRR (2017)
Samuel B. Hopkins, Pravesh K. Kothari, Aaron Potechin, Prasad Raghavendra, Tselil Schramm, David Steurer
The power of sum-of-squares for detecting hidden structures. CoRR (2017)
Prasad Raghavendra, Satish Rao, Tselil Schramm
Strongly refuting random CSPs below the spectral threshold. STOC (2017)
Samuel B. Hopkins, Pravesh K. Kothari, Aaron Potechin, Prasad Raghavendra, Tselil Schramm, David Steurer
The Power of Sum-of-Squares for Detecting Hidden Structures. FOCS (2017)
Ronen Eldan, Miklós Z. Rácz, Tselil Schramm
Braess's paradox for the spectral gap in random graphs and delocalization of eigenvectors. Random Struct. Algorithms 50 (4) (2017)
Tselil Schramm, David Steurer
Fast and robust tensor decomposition with applications to dictionary learning. COLT (2017)
Tselil Schramm, David Steurer
Fast and robust tensor decomposition with applications to dictionary learning. CoRR (2017)
Prasad Raghavendra, Satish Rao, Tselil Schramm
Strongly Refuting Random CSPs Below the Spectral Threshold. CoRR (2016)
Varun Kanade, Elchanan Mossel, Tselil Schramm
Global and Local Information in Clustering Labeled Block Models. IEEE Trans. Inf. Theory 62 (10) (2016)
Samuel B. Hopkins, Tselil Schramm, Jonathan Shi, David Steurer
Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors. STOC (2016)
Samuel B. Hopkins, Pravesh Kothari, Aaron Henry Potechin, Prasad Raghavendra, Tselil Schramm
On the Integrality Gap of Degree-4 Sum of Squares for Planted Clique. SODA (2016)
Tselil Schramm, Benjamin Weitz
Low-Rank Matrix Completion with Adversarial Missing Entries. CoRR (2015)
Prasad Raghavendra, Tselil Schramm
Tight Lower Bounds for Planted Clique in the Degree-4 SOS Program. CoRR (2015)
Shuchi Chawla, Konstantin Makarychev, Tselil Schramm, Grigory Yaroslavtsev
Near Optimal LP Rounding Algorithm for CorrelationClustering on Complete and Complete k-partite Graphs. STOC (2015)
Samuel B. Hopkins, Tselil Schramm, Jonathan Shi, David Steurer
Speeding up sum-of-squares for tensor decomposition and planted sparse vectors. CoRR (2015)
Varun Kanade, Elchanan Mossel, Tselil Schramm
Global and Local Information in Clustering Labeled Block Models. CoRR (2014)
Prasad Raghavendra, Tselil Schramm
Gap Amplification for Small-Set Expansion via Random Walks. APPROX-RANDOM (2014)
Shuchi Chawla, Konstantin Makarychev, Tselil Schramm, Grigory Yaroslavtsev
Near Optimal LP Rounding Algorithm for Correlation Clustering on Complete and Complete k-partite Graphs. CoRR (2014)
Varun Kanade, Elchanan Mossel, Tselil Schramm
Global and Local Information in Clustering Labeled Block Models. APPROX-RANDOM (2014)
Prasad Raghavendra, Tselil Schramm
Gap Amplification for Small-Set Expansion via Random Walks. CoRR (2013)