Reddi, Sashank J.

30 publications

ICML 2025 Bipartite Ranking from Multiple Labels: On Loss Versus Label Aggregation Michal Lukasik, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Felix X. Yu, Sashank J. Reddi, Gang Fu, Mohammadhossein Bateni, Sanjiv Kumar

ICLR 2025 Efficient Stagewise Pretraining via Progressive Subnetworks Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar

ICLR 2025 Reasoning with Latent Thoughts: On the Power of Looped Transformers Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li, Sanjiv Kumar, Sashank J. Reddi

ICML 2025 Structured Preconditioners in Adaptive Optimization: A Unified Analysis Shuo Xie, Tianhao Wang, Sashank J. Reddi, Sanjiv Kumar, Zhiyuan Li

ICML 2024 Can Looped Transformers Learn to Implement Multi-Step Gradient Descent for In-Context Learning? Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar

ICMLW 2024 Efficient Document Ranking with Learnable Late Interactions Himanshu Jain, Ziwei Ji, Sashank J. Reddi, Ankit Singh Rawat, Felix Yu, Aditya Krishna Menon, Sadeep Jayasumana

ICMLW 2024 Efficient Document Ranking with Learnable Late Interactions Himanshu Jain, Ziwei Ji, Ankit Singh Rawat, Andreas Veit, Sadeep Jayasumana, Sashank J. Reddi, Aditya Krishna Menon, Felix Yu

NeurIPS 2024 On the Inductive Bias of Stacking Towards Improving Reasoning Nikunj Saunshi, Stefani Karp, Shankar Krishnan, Sobhan Miryoosefi, Sashank J. Reddi, Sanjiv Kumar

ICML 2024 Simplicity Bias via Global Convergence of Sharpness Minimization Khashayar Gatmiry, Zhiyuan Li, Sashank J. Reddi, Stefanie Jegelka

ICLR 2023 Differentially Private Adaptive Optimization with Delayed Preconditioners Tian Li, Manzil Zaheer, Ken Liu, Sashank J. Reddi, Hugh Brendan McMahan, Virginia Smith

ICML 2023 Efficient Training of Language Models Using Few-Shot Learning Sashank J. Reddi, Sobhan Miryoosefi, Stefani Karp, Shankar Krishnan, Satyen Kale, Seungyeon Kim, Sanjiv Kumar

ICLR 2023 The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat, Sashank J. Reddi, Ke Ye, Felix Chern, Felix Yu, Ruiqi Guo, Sanjiv Kumar

NeurIPSW 2022 Differentially Private Adaptive Optimization with Delayed Preconditioners Tian Li, Manzil Zaheer, Ken Liu, Sashank J. Reddi, Hugh Brendan McMahan, Virginia Smith

ICLR 2021 Adaptive Federated Optimization Sashank J. Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečný, Sanjiv Kumar, Hugh Brendan McMahan

ICLR 2020 Are Transformers Universal Approximators of Sequence-to-Sequence Functions? Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar

ICLR 2020 Can Gradient Clipping Mitigate Label Noise? Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar

AISTATS 2019 Stochastic Negative Mining for Learning with Large Output Spaces Sashank J. Reddi, Satyen Kale, Felix Yu, Daniel Holtmann-Rice, Jiecao Chen, Sanjiv Kumar

AISTATS 2018 A Generic Approach for Escaping Saddle Points Sashank J. Reddi, Manzil Zaheer, Suvrit Sra, Barnabás Póczos, Francis R. Bach, Ruslan Salakhutdinov, Alexander J. Smola

ICLR 2018 On the Convergence of Adam and Beyond Sashank J. Reddi, Satyen Kale, Sanjiv Kumar

NeurIPS 2016 Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization Sashank J. Reddi, Suvrit Sra, Barnabas Poczos, Alexander J Smola

NeurIPS 2016 Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds Hongyi Zhang, Sashank J. Reddi, Suvrit Sra

ICML 2016 Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabas Poczos, Alex Smola

NeurIPS 2016 Variance Reduction in Stochastic Gradient Langevin Dynamics Kumar Avinava Dubey, Sashank J. Reddi, Sinead A Williamson, Barnabas Poczos, Alexander J Smola, Eric P Xing

UAI 2015 Communication Efficient Coresets for Empirical Loss Minimization Sashank J. Reddi, Barnabás Póczos, Alexander J. Smola

UAI 2015 Large-Scale Randomized-Coordinate Descent Methods with Non-Separable Linear Constraints Sashank J. Reddi, Ahmed Hefny, Carlton Downey, Avinava Dubey, Suvrit Sra

NeurIPS 2015 On Variance Reduction in Stochastic Gradient Descent and Its Asynchronous Variants Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabas Poczos, Alexander J Smola

AISTATS 2015 On the High Dimensional Power of a Linear-Time Two Sample Test Under Mean-Shift Alternatives Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman

UAI 2014 k-NN Regression on Functional Data with Incomplete Observations Sashank J. Reddi, Barnabás Póczos

ICML 2013 Scale Invariant Conditional Dependence Measures Sashank J Reddi, Barnabas Poczos

NeurIPS 2010 MAP Estimation in Binary MRFs via Bipartite Multi-Cuts Sashank J. Reddi, Sunita Sarawagi, Sundar Vishwanathan