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Praneeth Netrapalli

55 papers · 2013–2024 · 8 conferences · across top CS/AI conferences

Achievements

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+16 more ↓ 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (20) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8)
πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8) πŸ—ΊοΈ Taxonomy Completionist (20) 🏠 Conference Loyalist (20) 🀝 Dynamic Duo (31) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ† Grand Slam πŸ”¬ Deep Specialist (24) ❓ The Questioner (3) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (12) ⚑ Prolific Year (7) πŸ’Ž Century Club (55) πŸ—ƒοΈ Keyword Collector (61)

Conferences

NIPS (20) COLT (13) ICML (10) ICLR (5) JMLR (3) ALT (2) AAAI (1) AISTATS (1)

Research topics

Papers

The Feature Speed Formula: a flexible approach to scale hyper-parameters of deep neural networks NIPS 2024 Consistent Multiclass Algorithms for Complex Metrics and Constraints JMLR 2024 Tandem Transformers for Inference Efficient LLMs ICML 2024 Second Order Methods for Bandit Optimization and Control COLT 2024 Near Optimal Heteroscedastic Regression with Symbiotic Learning COLT 2023 Multi-User Reinforcement Learning with Low Rank Rewards ICML 2023 Simplicity Bias in 1-Hidden Layer Neural Networks NIPS 2023 Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks ICLR 2023 Focus on the Common Good: Group Distributional Robustness Follows ICLR 2022 Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs ICLR 2022 Reproducibility in Optimization: Theoretical Framework and Limits NIPS 2022 Minimax Optimization with Smooth Algorithmic Adversaries ICLR 2022 Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness NIPS 2021 Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization ICML 2021 Streaming Linear System Identification with Reverse Experience Replay NIPS 2021 Efficient Bandit Convex Optimization: Beyond Linear Losses COLT 2021 Do Input Gradients Highlight Discriminative Features? NIPS 2021 Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems NIPS 2021 Statistically and Computationally Efficient Linear Meta-representation Learning NIPS 2021 The Pitfalls of Simplicity Bias in Neural Networks NIPS 2020 Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms NIPS 2020 MOReL: Model-Based Offline Reinforcement Learning NIPS 2020 Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games NIPS 2020 P-SIF: Document Embeddings Using Partition Averaging AAAI 2020 What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization? ICML 2020 Leverage Score Sampling for Faster Accelerated Regression and ERM ALT 2020 Online Non-Convex Learning: Following the Perturbed Leader is Optimal ALT 2020 Efficient Domain Generalization via Common-Specific Low-Rank Decomposition ICML 2020 Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method NIPS 2020 The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares NIPS 2019 Efficient Algorithms for Smooth Minimax Optimization NIPS 2019 Making the Last Iterate of SGD Information Theoretically Optimal COLT 2019 Open Problem: Do Good Algorithms Necessarily Query Bad Points? COLT 2019 SGD without Replacement: Sharper Rates for General Smooth Convex Functions ICML 2019 Accelerated Gradient Descent Escapes Saddle Points Faster than Gradient Descent COLT 2018 Accelerating Stochastic Gradient Descent for Least Squares Regression COLT 2018 On the insufficiency of existing momentum schemes for Stochastic Optimization ICLR 2018 Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds NIPS 2018 Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form COLT 2018 Parallelizing Stochastic Gradient Descent for Least Squares Regression: Mini-batching, Averaging, and Model Misspecification JMLR 2018 Thresholding Based Outlier Robust PCA COLT 2017 Global Convergence of Non-Convex Gradient Descent for Computing Matrix Squareroot AISTATS 2017 How to Escape Saddle Points Efficiently ICML 2017 Information-theoretic thresholds for community detection in sparse networks COLT 2016 Faster Eigenvector Computation via Shift-and-Invert Preconditioning ICML 2016 Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis ICML 2016 Learning Planar Ising Models JMLR 2016 Provable Efficient Online Matrix Completion via Non-convex Stochastic Gradient Descent NIPS 2016 Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja’s Algorithm COLT 2016 Convergence Rates of Active Learning for Maximum Likelihood Estimation NIPS 2015 Fast Exact Matrix Completion with Finite Samples COLT 2015 Learning Sparsely Used Overcomplete Dictionaries COLT 2014 Non-convex Robust PCA NIPS 2014 One-Bit Compressed Sensing: Provable Support and Vector Recovery ICML 2013 Phase Retrieval using Alternating Minimization NIPS 2013