Ankur Moitra - RankMe

204 papers A* 80A 1B 2Journal 112Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Steering diffusion models with quadratic rewards: a fine-grained analysis. CoRR Ankur Moitra, Andrej Risteski, Dhruv Rohatgi
2026	J	`jnl`	Subliminal Effects in Your Data: A General Mechanism via Log-Linearity. CoRR Ishaq Aden-Ali, Noah Golowich, Allen Liu, Abhishek Shetty, Ankur Moitra, Nika Haghtalab
2025	J	`jnl`	A Dobrushin condition for quantum Markov chains: Rapid mixing and conditional mutual information at high temperature. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2025	J	`jnl`	Better Models and Algorithms for Learning Ising Models from Dynamics. CoRR Jason Gaitonde, Ankur Moitra, Elchanan Mossel
2025	A*	`conf`	Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics. STOC Jason Gaitonde, Ankur Moitra, Elchanan Mossel
2025	A*	`conf`	Conference on Learning Theory 2025: Preface. COLT Nika Haghtalab, Ankur Moitra
2025	J	`jnl`	Improved Pseudorandom Codes from Permuted Puzzles. CoRR Miranda Christ, Noah Golowich, Sam Gunn, Ankur Moitra, Daniel Wichs
2025	J	`jnl`	Improved Pseudorandom Codes from Permuted Puzzles. IACR Cryptol. ePrint Arch. Miranda Christ, Noah Golowich, Sam Gunn, Ankur Moitra, Daniel Wichs
2025	A*	`conf`	Model Stealing for Any Low-Rank Language Model. STOC Allen Liu, Ankur Moitra
2025	A*	`conf`	Overcomplete Tensor Decomposition via Koszul-Young Flattenings. FOCS Pravesh K. Kothari, Ankur Moitra, Alexander S. Wein
2025	J	`jnl`	Taming Imperfect Process Verifiers: A Sampling Perspective on Backtracking. CoRR Dhruv Rohatgi, Abhishek Shetty, Donya Saless, Yuchen Li, Ankur Moitra, Andrej Risteski, Dylan J. Foster
2025	A*	`ed.`	The Thirty Eighth Annual Conference on Learning Theory, 30-4 July 2025, Lyon, France. COLT Nika Haghtalab, Ankur Moitra
2025	A*	`conf`	Towards characterizing the value of edge embeddings in Graph Neural Networks. ICML Dhruv Rohatgi, Tanya Marwah, Zachary Chase Lipton, Jianfeng Lu, Ankur Moitra, Andrej Risteski
2024	J	`jnl`	Edit Distance Robust Watermarks for Language Models. CoRR Noah Golowich, Ankur Moitra
2024	J	`jnl`	Edit Distance Robust Watermarks for Language Models. IACR Cryptol. ePrint Arch. Noah Golowich, Ankur Moitra
2024	A*	`conf`	Edit Distance Robust Watermarks via Indexing Pseudorandom Codes. NeurIPS Noah Golowich, Ankur Moitra
2024	J	`jnl`	Efficiently Learning Markov Random Fields from Dynamics. CoRR Jason Gaitonde, Ankur Moitra, Elchanan Mossel
2024	A*	`conf`	Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning. FOCS Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2024	J	`jnl`	Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning. CoRR Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2024	A*	`conf`	Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles. STOC Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2024	J	`jnl`	Fast Sampling of Satisfying Assignments from Random \(\boldsymbol{k}\)-SAT with Applications to Connectivity. SIAM J. Discret. Math. Zongchen Chen, Andreas Galanis, Leslie Ann Goldberg, Heng Guo, Andrés Herrera-Poyatos, Nitya Mani, Ankur Moitra
2024	A*	`conf`	High-Temperature Gibbs States are Unentangled and Efficiently Preparable. FOCS Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2024	J	`jnl`	High-Temperature Gibbs States are Unentangled and Efficiently Preparable. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2024	A*	`conf`	Learning Quantum Hamiltonians at Any Temperature in Polynomial Time. STOC Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2024	A*	`conf`	Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions. COLT Noah Golowich, Ankur Moitra
2024	J	`jnl`	Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions. CoRR Noah Golowich, Ankur Moitra
2024	J	`jnl`	Model Stealing for Any Low-Rank Language Model. CoRR Allen Liu, Ankur Moitra
2024	J	`jnl`	On Learning Parities with Dependent Noise. CoRR Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2024	J	`jnl`	Overcomplete Tensor Decomposition via Koszul-Young Flattenings. CoRR Pravesh K. Kothari, Ankur Moitra, Alexander S. Wein
2024	A*	`conf`	Structure Learning of Hamiltonians from Real-Time Evolution. FOCS Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2024	J	`jnl`	Structure learning of Hamiltonians from real-time evolution. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2024	J	`jnl`	The Role of Inherent Bellman Error in Offline Reinforcement Learning with Linear Function Approximation. RLJ Noah Golowich, Ankur Moitra
2024	J	`jnl`	The Role of Inherent Bellman Error in Offline Reinforcement Learning with Linear Function Approximation. CoRR Noah Golowich, Ankur Moitra
2024	A*	`conf`	The power of an adversary in Glauber dynamics. COLT Byron Chin, Ankur Moitra, Elchanan Mossel, Colin Sandon
2024	J	`jnl`	Towards characterizing the value of edge embeddings in Graph Neural Networks. CoRR Dhruv Rohatgi, Tanya Marwah, Zachary Chase Lipton, Jianfeng Lu, Ankur Moitra, Andrej Risteski
2023	A*	`conf`	A New Approach to Learning Linear Dynamical Systems. STOC Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
2023	J	`jnl`	A New Approach to Learning Linear Dynamical Systems. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
2023	A*	`conf`	Distilling Model Failures as Directions in Latent Space. ICLR Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry
2023	J	`jnl`	Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles. CoRR Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2023	J	`jnl`	Learning quantum Hamiltonians at any temperature in polynomial time. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2023	A*	`conf`	Planning and Learning in Partially Observable Systems via Filter Stability. STOC Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2023	A*	`conf`	Provable benefits of score matching. NeurIPS Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski
2023	J	`jnl`	Provable benefits of score matching. CoRR Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski
2023	A*	`conf`	Provably Auditing Ordinary Least Squares in Low Dimensions. ICLR Ankur Moitra, Dhruv Rohatgi
2023	A*	`conf`	Robust Voting Rules from Algorithmic Robust Statistics. SODA Allen Liu, Ankur Moitra
2023	J	`jnl`	Robustly Learning General Mixtures of Gaussians. J. ACM Allen Liu, Ankur Moitra
2023	A*	`conf`	Strong Spatial Mixing for Colorings on Trees and its Algorithmic Applications. FOCS Zongchen Chen, Kuikui Liu, Nitya Mani, Ankur Moitra
2023	J	`jnl`	Strong spatial mixing for colorings on trees and its algorithmic applications. CoRR Zongchen Chen, Kuikui Liu, Nitya Mani, Ankur Moitra
2023	A*	`conf`	Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems. ICML Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
2023	J	`jnl`	Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
2022	A*	`conf`	Can Q-learning be Improved with Advice? COLT Noah Golowich, Ankur Moitra
2022	J	`jnl`	Distilling Model Failures as Directions in Latent Space. CoRR Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry
2022	J	`jnl`	From algorithms to connectivity and back: finding a giant component in random k-SAT. CoRR Zongchen Chen, Nitya Mani, Ankur Moitra
2022	A*	`conf`	Kalman filtering with adversarial corruptions. STOC Sitan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
2022	A*	`conf`	Learning GMMs with Nearly Optimal Robustness Guarantees. COLT Allen Liu, Ankur Moitra
2022	A*	`conf`	Learning in Observable POMDPs, without Computationally Intractable Oracles. NeurIPS Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2022	J	`jnl`	Learning in Observable POMDPs, without Computationally Intractable Oracles. CoRR Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2022	A*	`conf`	Minimax Rates for Robust Community Detection. FOCS Allen Liu, Ankur Moitra
2022	J	`jnl`	Minimax Rates for Robust Community Detection. CoRR Allen Liu, Ankur Moitra
2022	J	`jnl`	Noisy tensor completion via the sum-of-squares hierarchy. Math. Program. Boaz Barak, Ankur Moitra
2022	J	`jnl`	Planning in Observable POMDPs in Quasipolynomial Time. CoRR Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2022	A*	`conf`	Polynomial time guarantees for the Burer-Monteiro method. NeurIPS Diego Cifuentes, Ankur Moitra
2022	J	`jnl`	Provably Auditing Ordinary Least Squares in Low Dimensions. CoRR Ankur Moitra, Dhruv Rohatgi
2022	A*	`conf`	Robust Model Selection and Nearly-Proper Learning for GMMs. NeurIPS Allen Liu, Jerry Li, Ankur Moitra
2021	A*	`conf`	A No-go Theorem for Robust Acceleration in the Hyperbolic Plane. NeurIPS Linus Hamilton, Ankur Moitra
2021	A*	`conf`	Algorithmic foundations for the diffraction limit. STOC Sitan Chen, Ankur Moitra
2021	J	`jnl`	Can Q-Learning be Improved with Advice? CoRR Noah Golowich, Ankur Moitra
2021	J	`jnl`	How to Decompose a Tensor with Group Structure. CoRR Allen Liu, Ankur Moitra
2021	J	`jnl`	Kalman Filtering with Adversarial Corruptions. CoRR Sitan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
2021	J	`jnl`	Learning GMMs with Nearly Optimal Robustness Guarantees. CoRR Allen Liu, Ankur Moitra
2021	A*	`conf`	Learning to Sample from Censored Markov Random Fields. COLT Ankur Moitra, Elchanan Mossel, Colin Sandon
2021	J	`jnl`	Learning to Sample from Censored Markov Random Fields. CoRR Ankur Moitra, Elchanan Mossel, Colin Sandon
2021	J	`jnl`	No-go Theorem for Acceleration in the Hyperbolic Plane. CoRR Linus Hamilton, Ankur Moitra
2021	A*	`conf`	Online and Distribution-Free Robustness: Regression and Contextual Bandits with Huber Contamination. FOCS Sitan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
2021	J	`jnl`	Robust Voting Rules from Algorithmic Robust Statistics. CoRR Allen Liu, Ankur Moitra
2021	J	`jnl`	Robustness meets algorithms. Commun. ACM Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2021	A*	`conf`	Settling the robust learnability of mixtures of Gaussians. STOC Allen Liu, Ankur Moitra
2021	J	`jnl`	Sparsification for Sums of Exponentials and its Algorithmic Applications. CoRR Jerry Li, Allen Liu, Ankur Moitra
2021	J	`jnl`	Spoofing Generalization: When Can't You Trust Proprietary Models? CoRR Ankur Moitra, Elchanan Mossel, Colin Sandon
2020	J	`jnl`	Algorithmic Foundations for the Diffraction Limit. CoRR Sitan Chen, Ankur Moitra
2020	A*	`conf`	Better Algorithms for Estimating Non-Parametric Models in Crowd-Sourcing and Rank Aggregation. COLT Allen Liu, Ankur Moitra
2020	J	`jnl`	Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability. CoRR Sitan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
2020	A*	`conf`	Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Evolvability. NeurIPS Sitan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
2020	A*	`conf`	Efficiently learning structured distributions from untrusted batches. STOC Sitan Chen, Jerry Li, Ankur Moitra
2020	J	`jnl`	Fast Convergence for Langevin Diffusion with Matrix Manifold Structure. CoRR Ankur Moitra, Andrej Risteski
2020	J	`jnl`	How Many Subpopulations Is Too Many? Exponential Lower Bounds for Inferring Population Histories. J. Comput. Biol. Younhun Kim, Frederic Koehler, Ankur Moitra, Elchanan Mossel, Govind Ramnarayan
2020	A*	`conf`	Learning Some Popular Gaussian Graphical Models without Condition Number Bounds. NeurIPS Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Ankur Moitra
2020	A*	`conf`	Learning Structured Distributions From Untrusted Batches: Faster and Simpler. NeurIPS Sitan Chen, Jerry Li, Ankur Moitra
2020	J	`jnl`	Learning Structured Distributions From Untrusted Batches: Faster and Simpler. CoRR Sitan Chen, Jerry Li, Ankur Moitra
2020	J	`jnl`	Online and Distribution-Free Robustness: Regression and Contextual Bandits with Huber Contamination. CoRR Sitan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
2020	A*	`conf`	Parallels Between Phase Transitions and Circuit Complexity? COLT Ankur Moitra, Elchanan Mossel, Colin Sandon
2020	A*	`conf`	Rigorous Guarantees for Tyler's M-Estimator via Quantum Expansion. COLT William Cole Franks, Ankur Moitra
2020	J	`jnl`	Rigorous Guarantees for Tyler's M-estimator via quantum expansion. CoRR Cole Franks, Ankur Moitra
2020	—	`ch.`	Semirandom Stochastic Block Models. Beyond the Worst-Case Analysis of Algorithms Ankur Moitra
2020	J	`jnl`	Settling the Robust Learnability of Mixtures of Gaussians. CoRR Allen Liu, Ankur Moitra
2020	A*	`conf`	Tensor Completion Made Practical. NeurIPS Allen Liu, Ankur Moitra
2020	J	`jnl`	Tensor Completion Made Practical. CoRR Allen Liu, Ankur Moitra
2020	—	`ch.`	Topic Models and Nonnegative Matrix Factorization. Beyond the Worst-Case Analysis of Algorithms Rong Ge, Ankur Moitra
2019	J	`jnl`	A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem. SIAM J. Comput. Boaz Barak, Samuel B. Hopkins, Jonathan A. Kelner, Pravesh K. Kothari, Ankur Moitra, Aaron Potechin
2019	J	`jnl`	Approximate Counting, the Lovász Local Lemma, and Inference in Graphical Models. J. ACM Ankur Moitra
2019	A*	`conf`	Beyond the low-degree algorithm: mixtures of subcubes and their applications. STOC Sitan Chen, Ankur Moitra
2019	J	`jnl`	Efficiently Learning Structured Distributions from Untrusted Batches. CoRR Sitan Chen, Jerry Li, Ankur Moitra
2019	B	`conf`	How Many Subpopulations Is Too Many? Exponential Lower Bounds for Inferring Population Histories. RECOMB Younhun Kim, Frederic Koehler, Ankur Moitra, Elchanan Mossel, Govind Ramnarayan
2019	A*	`conf`	Improved Bounds for Randomly Sampling Colorings via Linear Programming. SODA Sitan Chen, Michelle Delcourt, Ankur Moitra, Guillem Perarnau, Luke Postle
2019	J	`jnl`	Learning Some Popular Gaussian Graphical Models without Condition Number Bounds. CoRR Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Ankur Moitra
2019	A*	`conf`	Learning restricted Boltzmann machines via influence maximization. STOC Guy Bresler, Frederic Koehler, Ankur Moitra
2019	J	`jnl`	Robust Estimators in High-Dimensions Without the Computational Intractability. SIAM J. Comput. Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2019	J	`jnl`	Spectral Methods from Tensor Networks. SIAM J. Comput. Ankur Moitra, Alexander S. Wein
2019	A*	`conf`	Spectral methods from tensor networks. STOC Ankur Moitra, Alexander S. Wein
2019	J	`jnl`	The Circuit Complexity of Inference. CoRR Ankur Moitra, Elchanan Mossel, Colin Sandon
2019	A	`conf`	The Paulsen Problem Made Simple. ITCS Linus Hamilton, Ankur Moitra
2018	A*	`conf`	Efficiently Learning Mixtures of Mallows Models. FOCS Allen Liu, Ankur Moitra
2018	J	`jnl`	Efficiently Learning Mixtures of Mallows Models. CoRR Allen Liu, Ankur Moitra
2018	J	`jnl`	Improved Bounds for Randomly Sampling Colorings via Linear Programming. CoRR Sitan Chen, Michelle Delcourt, Ankur Moitra, Guillem Perarnau, Luke Postle
2018	J	`jnl`	Learning Mixtures of Product Distributions via Higher Multilinear Moments. CoRR Sitan Chen, Ankur Moitra
2018	J	`jnl`	Learning Restricted Boltzmann Machines via Influence Maximization. CoRR Guy Bresler, Frederic Koehler, Ankur Moitra, Elchanan Mossel
2018	J	`jnl`	Learning topic models - provably and efficiently. Commun. ACM Sanjeev Arora, Rong Ge, Yoni Halpern, David M. Mimno, Ankur Moitra, David A. Sontag, Yichen Wu, Michael Zhu
2018	J	`jnl`	Linear Programming Bounds for Randomly Sampling Colorings. CoRR Sitan Chen, Ankur Moitra
2018	J	`jnl`	Optimality and Sub-optimality of PCA I: Spiked Random Matrix Models. CoRR Amelia Perry, Alexander S. Wein, Afonso S. Bandeira, Ankur Moitra
2018	A*	`conf`	Robustly Learning a Gaussian: Getting Optimal Error, Efficiently. SODA Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2018	—	`conf`	Robustness Meets Algorithms (Invited Talk). SWAT Ankur Moitra
2018	J	`jnl`	Spectral Methods from Tensor Networks. CoRR Ankur Moitra, Alexander S. Wein
2018	J	`jnl`	The Paulsen Problem Made Simple. CoRR Linus Hamilton, Ankur Moitra
2017	A*	`conf`	Approximate counting, the Lovasz local lemma, and inference in graphical models. STOC Ankur Moitra
2017	A*	`conf`	Being Robust (in High Dimensions) Can Be Practical. ICML Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2017	J	`jnl`	Being Robust (in High Dimensions) Can Be Practical. CoRR Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2017	—	`conf`	Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications. NIPS Linus Hamilton, Frederic Koehler, Ankur Moitra
2017	J	`jnl`	Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications. CoRR Linus Hamilton, Frederic Koehler, Ankur Moitra
2017	A*	`conf`	Learning Determinantal Point Processes with Moments and Cycles. ICML John Urschel, Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet
2017	A*	`conf`	Rates of estimation for determinantal point processes. COLT Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet, John Urschel
2017	J	`jnl`	Robustly Learning a Gaussian: Getting Optimal Error, Efficiently. CoRR Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2016	A*	`conf`	A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem. FOCS Boaz Barak, Samuel B. Hopkins, Jonathan A. Kelner, Pravesh Kothari, Ankur Moitra, Aaron Potechin
2016	J	`jnl`	A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem. CoRR Boaz Barak, Samuel B. Hopkins, Jonathan A. Kelner, Pravesh Kothari, Ankur Moitra, Aaron Potechin
2016	J	`jnl`	A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem. Electron. Colloquium Comput. Complex. Boaz Barak, Samuel B. Hopkins, Jonathan A. Kelner, Pravesh Kothari, Ankur Moitra, Aaron Potechin
2016	J	`jnl`	An Almost Optimal Algorithm for Computing Nonnegative Rank. SIAM J. Comput. Ankur Moitra
2016	J	`jnl`	Approximate Counting, the Lovasz Local Lemma and Inference in Graphical Models. CoRR Ankur Moitra
2016	J	`jnl`	Computing a Nonnegative Matrix Factorization - Provably. SIAM J. Comput. Sanjeev Arora, Rong Ge, Ravi Kannan, Ankur Moitra
2016	A*	`conf`	How robust are reconstruction thresholds for community detection? STOC Ankur Moitra, William Perry, Alexander S. Wein
2016	J	`jnl`	Message-passing algorithms for synchronization problems over compact groups. CoRR Amelia Perry, Alexander S. Wein, Afonso S. Bandeira, Ankur Moitra
2016	A*	`conf`	Noisy Tensor Completion via the Sum-of-Squares Hierarchy. COLT Boaz Barak, Ankur Moitra
2016	J	`jnl`	Optimality and Sub-optimality of PCA for Spiked Random Matrices and Synchronization. CoRR Amelia Perry, Alexander S. Wein, Afonso S. Bandeira, Ankur Moitra
2016	A*	`conf`	Provable Algorithms for Inference in Topic Models. ICML Sanjeev Arora, Rong Ge, Frederic Koehler, Tengyu Ma, Ankur Moitra
2016	J	`jnl`	Provable Algorithms for Inference in Topic Models. CoRR Sanjeev Arora, Rong Ge, Frederic Koehler, Tengyu Ma, Ankur Moitra
2016	A*	`conf`	Robust Estimators in High Dimensions without the Computational Intractability. FOCS Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2016	J	`jnl`	Robust Estimators in High Dimensions without the Computational Intractability. CoRR Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Zheng Li, Ankur Moitra, Alistair Stewart
2015	—	`conf`	Beating the Random Assignment on Constraint Satisfaction Problems of Bounded Degree. APPROX-RANDOM Boaz Barak, Ankur Moitra, Ryan O'Donnell, Prasad Raghavendra, Oded Regev, David Steurer, Luca Trevisan, Aravindan Vijayaraghavan, David Witmer, John Wright
2015	J	`jnl`	Beating the random assignment on constraint satisfaction problems of bounded degree. CoRR Boaz Barak, Ankur Moitra, Ryan O'Donnell, Prasad Raghavendra, Oded Regev, David Steurer, Luca Trevisan, Aravindan Vijayaraghavan, David Witmer, John Wright
2015	J	`jnl`	Beating the random assignment on constraint satisfaction problems of bounded degree. Electron. Colloquium Comput. Complex. Boaz Barak, Ankur Moitra, Ryan O'Donnell, Prasad Raghavendra, Oded Regev, David Steurer, Luca Trevisan, Aravindan Vijayaraghavan, David Witmer, John Wright
2015	—	`conf`	Beyond Matrix Completion (Invited Talk). FSTTCS Ankur Moitra
2015	J	`jnl`	How Robust are Reconstruction Thresholds for Community Detection? CoRR Ankur Moitra, William Perry, Alexander S. Wein
2015	B	`conf`	Nonnegative Matrix Factorization: Algorithms, Complexity and Applications. ISSAC Ankur Moitra
2015	J	`jnl`	Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders. Algorithmica Sanjeev Arora, Rong Ge, Ankur Moitra, Sushant Sachdeva
2015	A*	`conf`	Simple, Efficient, and Neural Algorithms for Sparse Coding. COLT Sanjeev Arora, Rong Ge, Tengyu Ma, Ankur Moitra
2015	J	`jnl`	Simple, Efficient, and Neural Algorithms for Sparse Coding. CoRR Sanjeev Arora, Rong Ge, Tengyu Ma, Ankur Moitra
2015	A*	`conf`	Super-resolution, Extremal Functions and the Condition Number of Vandermonde Matrices. STOC Ankur Moitra
2015	J	`jnl`	Tensor Prediction, Rademacher Complexity and Random 3-XOR. CoRR Boaz Barak, Ankur Moitra
2014	A*	`conf`	A Polynomial-time Approximation Scheme for Fault-tolerant Distributed Storage. SODA Constantinos Daskalakis, Anindya De, Ilias Diakonikolas, Ankur Moitra, Rocco A. Servedio
2014	J	`jnl`	Efficient Coding for Interactive Communication. IEEE Trans. Inf. Theory Ran Gelles, Ankur Moitra, Amit Sahai
2014	A*	`conf`	New Algorithms for Learning Incoherent and Overcomplete Dictionaries. COLT Sanjeev Arora, Rong Ge, Ankur Moitra
2014	A*	`conf`	Open Problem: Tensor Decompositions: Algorithms up to the Uniqueness Threshold? COLT Aditya Bhaskara, Moses Charikar, Ankur Moitra, Aravindan Vijayaraghavan
2014	A*	`conf`	Smoothed analysis of tensor decompositions. STOC Aditya Bhaskara, Moses Charikar, Ankur Moitra, Aravindan Vijayaraghavan
2014	J	`jnl`	The Threshold for Super-resolution via Extremal Functions. CoRR Ankur Moitra
2013	J	`jnl`	A Polynomial Time Algorithm for Lossy Population Recovery CoRR Ankur Moitra, Michael E. Saks
2013	A*	`conf`	A Polynomial Time Algorithm for Lossy Population Recovery. FOCS Ankur Moitra, Michael E. Saks
2013	J	`jnl`	A Polynomial-time Approximation Scheme for Fault-tolerant Distributed Storage. CoRR Constantinos Daskalakis, Anindya De, Ilias Diakonikolas, Ankur Moitra, Rocco A. Servedio
2013	—	`conf`	A Practical Algorithm for Topic Modeling with Provable Guarantees. ICML (2) Sanjeev Arora, Rong Ge, Yonatan Halpern, David M. Mimno, Ankur Moitra, David A. Sontag, Yichen Wu, Michael Zhu
2013	A*	`conf`	Algorithms and Hardness for Robust Subspace Recovery. COLT Moritz Hardt, Ankur Moitra
2013	A*	`conf`	An Almost Optimal Algorithm for Computing Nonnegative Rank. SODA Ankur Moitra
2013	A*	`conf`	An information complexity approach to extended formulations. STOC Mark Braverman, Ankur Moitra
2013	J	`jnl`	New Algorithms for Learning Incoherent and Overcomplete Dictionaries. CoRR Sanjeev Arora, Rong Ge, Ankur Moitra
2013	J	`jnl`	Smoothed Analysis of Tensor Decompositions. CoRR Aditya Bhaskara, Moses Charikar, Ankur Moitra, Aravindan Vijayaraghavan
2013	J	`jnl`	Vertex Sparsification and Oblivious Reductions. SIAM J. Comput. Ankur Moitra
2012	—	`conf`	"Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders". NIPS Sanjeev Arora, Rong Ge, Ankur Moitra, Sushant Sachdeva
2012	J	`jnl`	A Practical Algorithm for Topic Modeling with Provable Guarantees CoRR Sanjeev Arora, Rong Ge, Yoni Halpern, David M. Mimno, Ankur Moitra, David A. Sontag, Yichen Wu, Michael Zhu
2012	J	`jnl`	A Singly-Exponential Time Algorithm for Computing Nonnegative Rank CoRR Ankur Moitra
2012	J	`jnl`	A Singly-Exponential Time Algorithm for Computing Nonnegative Rank. Electron. Colloquium Comput. Complex. Ankur Moitra
2012	J	`jnl`	An Information Complexity Approach to Extended Formulations. Electron. Colloquium Comput. Complex. Mark Braverman, Ankur Moitra
2012	J	`jnl`	Can We Reconcile Robustness and Efficiency in Unsupervised Learning? CoRR Moritz Hardt, Ankur Moitra
2012	A*	`conf`	Computing a nonnegative matrix factorization - provably. STOC Sanjeev Arora, Rong Ge, Ravindran Kannan, Ankur Moitra
2012	J	`jnl`	Disentangling Gaussians. Commun. ACM Adam Tauman Kalai, Ankur Moitra, Gregory Valiant
2012	J	`jnl`	Learning Topic Models - Going beyond SVD CoRR Sanjeev Arora, Rong Ge, Ankur Moitra
2012	A*	`conf`	Learning Topic Models - Going beyond SVD. FOCS Sanjeev Arora, Rong Ge, Ankur Moitra
2012	A*	`conf`	Nearly complete graphs decomposable into large induced matchings and their applications. STOC Noga Alon, Ankur Moitra, Benny Sudakov
2012	J	`jnl`	Pareto Optimal Solutions for Smoothed Analysts. SIAM J. Comput. Ankur Moitra, Ryan O'Donnell
2012	J	`jnl`	Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders CoRR Sanjeev Arora, Rong Ge, Ankur Moitra, Sushant Sachdeva
2011	A*	`conf`	Capacitated Metric Labeling. SODA Matthew Andrews, Mohammad Taghi Hajiaghayi, Howard J. Karloff, Ankur Moitra
2011	J	`jnl`	Computing a Nonnegative Matrix Factorization -- Provably CoRR Sanjeev Arora, Rong Ge, Ravi Kannan, Ankur Moitra
2011	J	`jnl`	Dueling Algorithms CoRR Nicole Immorlica, Adam Tauman Kalai, Brendan Lucier, Ankur Moitra, Andrew Postlewaite, Moshe Tennenholtz
2011	A*	`conf`	Dueling algorithms. STOC Nicole Immorlica, Adam Tauman Kalai, Brendan Lucier, Ankur Moitra, Andrew Postlewaite, Moshe Tennenholtz
2011	A*	`conf`	Efficient and Explicit Coding for Interactive Communication. FOCS Ran Gelles, Ankur Moitra, Amit Sahai
2011	J	`jnl`	Efficiently Coding for Interactive Communication. Electron. Colloquium Comput. Complex. Ankur Moitra
2011	J	`jnl`	Nearly Complete Graphs Decomposable into Large Induced Matchings and their Applications CoRR Noga Alon, Ankur Moitra, Benny Sudakov
2011	A*	`conf`	Pareto optimal solutions for smoothed analysts. STOC Ankur Moitra, Ryan O'Donnell
2011	—	`—`	Vertex sparsification and universal rounding algorithms. Ankur Moitra
2010	A*	`conf`	Efficiently learning mixtures of two Gaussians. STOC Adam Tauman Kalai, Ankur Moitra, Gregory Valiant
2010	A*	`conf`	Extensions and limits to vertex sparsification. STOC Frank Thomson Leighton, Ankur Moitra
2010	J	`jnl`	Pareto Optimal Solutions for Smoothed Analysts CoRR Ankur Moitra, Ryan O'Donnell
2010	J	`jnl`	Settling the Polynomial Learnability of Mixtures of Gaussians CoRR Ankur Moitra, Gregory Valiant
2010	A*	`conf`	Settling the Polynomial Learnability of Mixtures of Gaussians. FOCS Ankur Moitra, Gregory Valiant
2010	J	`jnl`	Some Results on Greedy Embeddings in Metric Spaces. Discret. Comput. Geom. Tom Leighton, Ankur Moitra
2010	J	`jnl`	Vertex Sparsifiers and Abstract Rounding Algorithms CoRR Moses Charikar, Tom Leighton, Shi Li, Ankur Moitra
2010	A*	`conf`	Vertex Sparsifiers and Abstract Rounding Algorithms. FOCS Moses Charikar, Tom Leighton, Shi Li, Ankur Moitra
2009	A*	`conf`	Approximation Algorithms for Multicommodity-Type Problems with Guarantees Independent of the Graph Size. FOCS Ankur Moitra
2008	A*	`conf`	Some Results on Greedy Embeddings in Metric Spaces. FOCS Ankur Moitra, Tom Leighton