Sashank J. Reddi
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
33
Venues
4
Active years
2013–2025
Best venue rank
A*
Where they publish
Papers
33 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Efficient stagewise pretraining via progressive subnetworks. | Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar |
| 2025 | ICLR | Reasoning with Latent Thoughts: On the Power of Looped Transformers. | Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li, Sanjiv Kumar, Sashank J. Reddi |
| 2025 | ICML | 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 |
| 2025 | ICML | Structured Preconditioners in Adaptive Optimization: A Unified Analysis. | Shuo Xie, Tianhao Wang, Sashank J. Reddi, Sanjiv Kumar, Zhiyuan Li |
| 2024 | ICML | Simplicity Bias via Global Convergence of Sharpness Minimization. | Khashayar Gatmiry, Zhiyuan Li, Sashank J. Reddi, Stefanie Jegelka |
| 2024 | ICML | 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 |
| 2023 | ICLR | Differentially Private Adaptive Optimization with Delayed Preconditioners. | Tian Li, Manzil Zaheer, Ken Liu, Sashank J. Reddi, Hugh Brendan McMahan, Virginia Smith |
| 2023 | ICLR | 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 X. Yu, Ruiqi Guo, Sanjiv Kumar |
| 2023 | ICML | Efficient Training of Language Models using Few-Shot Learning. | Sashank J. Reddi, Sobhan Miryoosefi, Stefani Karp, Shankar Krishnan, Satyen Kale, Seungyeon Kim, Sanjiv Kumar |
| 2022 | ICML | Robust Training of Neural Networks Using Scale Invariant Architectures. | Zhiyuan Li, Srinadh Bhojanapalli, Manzil Zaheer, Sashank J. Reddi, Sanjiv Kumar |
| 2022 | ICML | Private Adaptive Optimization with Side information. | Tian Li, Manzil Zaheer, Sashank J. Reddi, Virginia Smith |
| 2022 | ICML | In defense of dual-encoders for neural ranking. | Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar |
| 2021 | AISTATS | RankDistil: Knowledge Distillation for Ranking. | Sashank J. Reddi, Rama Kumar Pasumarthi, Aditya Krishna Menon, Ankit Singh Rawat, Felix X. Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar |
| 2021 | ICLR | Adaptive Federated Optimization. | Sashank J. Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konecn, Sanjiv Kumar, Hugh Brendan McMahan |
| 2021 | ICML | A statistical perspective on distillation. | Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar |
| 2021 | ICML | Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces. | Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar |
| 2021 | ICML | Federated Composite Optimization. | Honglin Yuan, Manzil Zaheer, Sashank J. Reddi |
| 2020 | ICLR | Can gradient clipping mitigate label noise? | Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar |
| 2020 | ICLR | Learning to Learn by Zeroth-Order Oracle. | Yangjun Ruan, Yuanhao Xiong, Sashank J. Reddi, Sanjiv Kumar, Cho-Jui Hsieh |
| 2020 | ICLR | Large Batch Optimization for Deep Learning: Training BERT in 76 minutes. | Yang You, Jing Li, Sashank J. Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, Cho-Jui Hsieh |
| 2020 | ICLR | Are Transformers universal approximators of sequence-to-sequence functions? | Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar |
| 2020 | ICML | Low-Rank Bottleneck in Multi-head Attention Models. | Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar |
| 2020 | ICML | SCAFFOLD: Stochastic Controlled Averaging for Federated Learning. | Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh |
| 2019 | AISTATS | Stochastic Negative Mining for Learning with Large Output Spaces. | Sashank J. Reddi, Satyen Kale, Felix X. Yu, Daniel Niels Holtmann-Rice, Jiecao Chen, Sanjiv Kumar |
| 2019 | ICML | Escaping Saddle Points with Adaptive Gradient Methods. | Matthew Staib, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar, Suvrit Sra |
| 2018 | AISTATS | A Generic Approach for Escaping Saddle points. | Sashank J. Reddi, Manzil Zaheer, Suvrit Sra, Barnabs Pczos, Francis R. Bach, Ruslan Salakhutdinov, Alexander J. Smola |
| 2018 | ICLR | On the Convergence of Adam and Beyond. | Sashank J. Reddi, Satyen Kale, Sanjiv Kumar |
| 2016 | ICML | Stochastic Variance Reduction for Nonconvex Optimization. | Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabs Pczos, Alexander J. Smola |
| 2015 | AISTATS | On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives. | Sashank J. Reddi, Aaditya Ramdas, Barnabs Pczos, Aarti Singh, Larry A. Wasserman |
| 2015 | UAI | Large-scale randomized-coordinate descent methods with non-separable linear constraints. | Sashank J. Reddi, Ahmed Hefny, Carlton Downey, Avinava Dubey, Suvrit Sra |
| 2015 | UAI | Communication Efficient Coresets for Empirical Loss Minimization. | Sashank J. Reddi, Barnabs Pczos, Alexander J. Smola |
| 2014 | UAI | k-NN Regression on Functional Data with Incomplete Observations. | Sashank J. Reddi, Barnabs Pczos |
| 2013 | ICML | Scale Invariant Conditional Dependence Measures. | Sashank J. Reddi, Barnabs Pczos |