Sharan, Vatsal

34 publications

NeurIPS 2025 Discovering Data Structures: Nearest Neighbor Search and Beyond Omar Salemohamed, Laurent Charlin, Shivam Garg, Vatsal Sharan, Gregory Valiant

NeurIPS 2025 Improved Bounds for Swap Multicalibration and Swap Omniprediction Haipeng Luo, Spandan Senapati, Vatsal Sharan

AISTATS 2025 On the Inherent Privacy of Zeroth-Order Projected Gradient Descent Devansh Gupta, Meisam Razaviyayn, Vatsal Sharan

ALT 2025 Proper Learnability and the Role of Unlabeled Data Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

NeurIPS 2025 Simultaneous Swap Regret Minimization via KL-Calibration Haipeng Luo, Spandan Senapati, Vatsal Sharan

NeurIPS 2025 The Rich and the Simple: On the Implicit Bias of Adam and SGD Bhavya Vasudeva, Jung Whan Lee, Vatsal Sharan, Mahdi Soltanolkotabi

ICLR 2025 Transformers Learn Low Sensitivity Functions: Investigations and Implications Bhavya Vasudeva, Deqing Fu, Tianyi Zhou, Elliott Kau, Youqi Huang, Vatsal Sharan

NeurIPSW 2024 Implicit Bias of Adam Versus Gradient Descent in One-Hidden-Layer Neural Networks Bhavya Vasudeva, Vatsal Sharan, Mahdi Soltanolkotabi

ICMLW 2024 Learning to Design Data-Structures: A Case Study of Nearest Neighbor Search Omar Salemohamed, Vatsal Sharan, Shivam Garg, Laurent Charlin, Gregory Valiant

TMLR 2024 Mitigating Simplicity Bias in Deep Learning for Improved OOD Generalization and Robustness Bhavya Vasudeva, Kameron Shahabi, Vatsal Sharan

NeurIPSW 2024 On the Inherent Privacy of Two Point Zeroth Order Projected Gradient Descent Devansh Gupta, Meisam Razaviyayn, Vatsal Sharan

COLT 2024 Open Problem: Can Local Regularization Learn All Multiclass Problems? Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

NeurIPS 2024 Optimal Multiclass U-Calibration Error and Beyond Haipeng Luo, Spandan Senapati, Vatsal Sharan

NeurIPS 2024 Pre-Trained Large Language Models Use Fourier Features to Compute Addition Tianyi Zhou, Deqing Fu, Vatsal Sharan, Robin Jia

COLT 2024 Regularization and Optimal Multiclass Learning Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

ICML 2024 Stability and Multigroup Fairness in Ranking with Uncertain Predictions Siddartha Devic, Aleksandra Korolova, David Kempe, Vatsal Sharan

NeurIPS 2024 Transductive Learning Is Compact Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

NeurIPS 2024 Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression Deqing Fu, Tian-Qi Chen, Robin Jia, Vatsal Sharan

NeurIPS 2024 When Is Multicalibration Post-Processing Necessary? Dutch Hansen, Siddartha Devic, Preetum Nakkiran, Vatsal Sharan

IJCAI 2023 Efficient Convex Optimization Requires Superlinear Memory (Extended Abstract) Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant

ICML 2023 Fairness in Matching Under Uncertainty Siddartha Devic, David Kempe, Vatsal Sharan, Aleksandra Korolova

NeurIPSW 2023 Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Models Deqing Fu, Tianqi Chen, Robin Jia, Vatsal Sharan

COLT 2022 Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales Jonathan Kelner, Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant, Honglin Yuan

COLT 2022 Efficient Convex Optimization Requires Superlinear Memory Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant

ALT 2022 Multicalibrated Partitions for Importance Weights Parikshit Gopalan, Omer Reingold, Vatsal Sharan, Udi Wieder

ICLR 2021 One Network Fits All? Modular Versus Monolithic Task Formulations in Neural Networks Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang

ICML 2020 Sample Amplification: Increasing Dataset Size Even When Learning Is Impossible Brian Axelrod, Shivam Garg, Vatsal Sharan, Gregory Valiant

ICML 2019 Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data Vatsal Sharan, Kai Sheng Tai, Peter Bailis, Gregory Valiant

NeurIPS 2019 PIDForest: Anomaly Detection via Partial Identification Parikshit Gopalan, Vatsal Sharan, Udi Wieder

AISTATS 2019 Recovery Guarantees for Quadratic Tensors with Sparse Observations Hongyang Zhang, Vatsal Sharan, Moses Charikar, Yingyu Liang

NeurIPS 2018 A Spectral View of Adversarially Robust Features Shivam Garg, Vatsal Sharan, Brian Zhang, Gregory Valiant

NeurIPS 2018 Efficient Anomaly Detection via Matrix Sketching Vatsal Sharan, Parikshit Gopalan, Udi Wieder

NeurIPS 2017 Learning Overcomplete HMMs Vatsal Sharan, Sham M. Kakade, Percy Liang, Gregory Valiant

ICML 2017 Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use Vatsal Sharan, Gregory Valiant