Praneeth Netrapalli
According to our database1,
Praneeth Netrapalli
authored at least 91 papers
between 2010 and 2024.
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Bibliography
2024
CoRR, 2024
All Mistakes are not Equal: Comprehensive Hierarchy Aware Multilabel Predictions (CHAMP).
Proceedings of the Pattern Recognition - 27th International Conference, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024
2023
Optimistic MLE: A Generic Model-Based Algorithm for Partially Observable Sequential Decision Making.
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
2022
Learning an Invertible Output Mapping Can Mitigate Simplicity Bias in Neural Networks.
CoRR, 2022
CoRR, 2022
All Mistakes Are Not Equal: Comprehensive Hierarchy Aware Multi-label Predictions (CHAMP).
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs.
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
SIAM J. Optim., 2021
On Nonconvex Optimization for Machine Learning: Gradients, Stochasticity, and Saddle Points.
J. ACM, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 12th Innovations in Theoretical Computer Science Conference, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the Conference on Learning Theory, 2021
2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the Algorithmic Learning Theory, 2020
Proceedings of the Algorithmic Learning Theory, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure.
CoRR, 2019
CoRR, 2019
Minmax Optimization: Stable Limit Points of Gradient Descent Ascent are Locally Optimal.
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the Conference on Learning Theory, 2019
2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
Proceedings of the Conference On Learning Theory, 2018
Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form.
Proceedings of the Conference On Learning Theory, 2018
Proceedings of the Conference On Learning Theory, 2018
2017
IEEE Trans. Inf. Theory, 2017
Parallelizing Stochastic Gradient Descent for Least Squares Regression: Mini-batching, Averaging, and Model Misspecification.
J. Mach. Learn. Res., 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares).
Proceedings of the 37th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, 2017
Proceedings of the 30th Conference on Learning Theory, 2017
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
SIAM J. Optim., 2016
CoRR, 2016
Matching Matrix Bernstein with Little Memory: Near-Optimal Finite Sample Guarantees for Oja's Algorithm.
CoRR, 2016
Provable Efficient Online Matrix Completion via Non-convex Stochastic Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm.
Proceedings of the 29th Conference on Learning Theory, 2016
Proceedings of the 29th Conference on Learning Theory, 2016
2015
Robust Shift-and-Invert Preconditioning: Faster and More Sample Efficient Algorithms for Eigenvector Computation.
CoRR, 2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of The 28th Conference on Learning Theory, 2015
2014
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014
Proceedings of The 27th Conference on Learning Theory, 2014
2013
CoRR, 2013
Proceedings of the Symposium on Theory of Computing Conference, 2013
Proceedings of the 30th International Conference on Machine Learning, 2013
2012
Proceedings of the ACM SIGMETRICS/PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems, 2012
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012
2010
Proceedings of the 48th Annual Allerton Conference on Communication, 2010