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Sanjiv Kumar

Google Research

Teacher's pet: understanding and mitigating biases in distillation


Jul 08, 2021
Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar

* 21 pages, 8 figures 

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Eigen Analysis of Self-Attention and its Reconstruction from Partial Computation


Jun 16, 2021
Srinadh Bhojanapalli, Ayan Chakrabarti, Himanshu Jain, Sanjiv Kumar, Michal Lukasik, Andreas Veit

* 14 pages 

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Scaling Hierarchical Agglomerative Clustering to Billion-sized Datasets


May 25, 2021
Baris Sumengen, Anand Rajagopalan, Gui Citovsky, David Simcha, Olivier Bachem, Pradipta Mitra, Sam Blasiak, Mason Liang, Sanjiv Kumar

* 19 pages, 3 figures 

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Balancing Robustness and Sensitivity using Feature Contrastive Learning


May 19, 2021
Seungyeon Kim, Daniel Glasner, Srikumar Ramalingam, Cho-Jui Hsieh, Kishore Papineni, Sanjiv Kumar

* 31 pages, 5 figures, 3 tables 

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Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces


May 12, 2021
Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank Reddi, Sanjiv Kumar

* To appear in ICML 2021 

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Balancing Constraints and Submodularity in Data Subset Selection


Apr 26, 2021
Srikumar Ramalingam, Daniel Glasner, Kaushal Patel, Raviteja Vemulapalli, Sadeep Jayasumana, Sanjiv Kumar


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On the Reproducibility of Neural Network Predictions


Feb 05, 2021
Srinadh Bhojanapalli, Kimberly Wilber, Andreas Veit, Ankit Singh Rawat, Seungyeon Kim, Aditya Menon, Sanjiv Kumar

* 19 pages, 7 figures 

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Kernelized Classification in Deep Networks


Dec 08, 2020
Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar


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Modifying Memories in Transformer Models


Dec 01, 2020
Chen Zhu, Ankit Singh Rawat, Manzil Zaheer, Srinadh Bhojanapalli, Daliang Li, Felix Yu, Sanjiv Kumar


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Coping with Label Shift via Distributionally Robust Optimisation


Oct 23, 2020
Jingzhao Zhang, Aditya Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra


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Semantic Label Smoothing for Sequence to Sequence Problems


Oct 15, 2020
Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix Yu, Sanjiv Kumar


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Learning discrete distributions: user vs item-level privacy


Jul 28, 2020
Yuhan Liu, Ananda Theertha Suresh, Felix Yu, Sanjiv Kumar, Michael Riley

* 36 pages 

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Learning discrete distributions: user-lever vs item-level privacy


Jul 27, 2020
Yuhan Liu, Ananda Theertha Suresh, Felix Yu, Sanjiv Kumar, Michael Riley

* 36 pages 

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Multi-Stage Influence Function


Jul 17, 2020
Hongge Chen, Si Si, Yang Li, Ciprian Chelba, Sanjiv Kumar, Duane Boning, Cho-Jui Hsieh


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Long-tail learning via logit adjustment


Jul 14, 2020
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar


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$O(n)$ Connections are Expressive Enough: Universal Approximability of Sparse Transformers


Jun 08, 2020
Chulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar

* 32 pages 

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Evaluations and Methods for Explanation through Robustness Analysis


May 31, 2020
Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh


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Why distillation helps: a statistical perspective


May 21, 2020
Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar


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Doubly-stochastic mining for heterogeneous retrieval


Apr 23, 2020
Ankit Singh Rawat, Aditya Krishna Menon, Andreas Veit, Felix Yu, Sashank J. Reddi, Sanjiv Kumar


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Federated Learning with Only Positive Labels


Apr 21, 2020
Felix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar


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Robust Large-Margin Learning in Hyperbolic Space


Apr 11, 2020
Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Menon, Sanjiv Kumar

* Under Review 

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Does label smoothing mitigate label noise?


Mar 05, 2020
Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar


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Adaptive Federated Optimization


Feb 29, 2020
Sashank Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečný, Sanjiv Kumar, H. Brendan McMahan


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Low-Rank Bottleneck in Multi-head Attention Models


Feb 17, 2020
Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar

* 17 pages, 4 figures 

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Pre-training Tasks for Embedding-based Large-scale Retrieval


Feb 10, 2020
Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar

* Accepted by ICLR 2020 

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Are Transformers universal approximators of sequence-to-sequence functions?


Dec 20, 2019
Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar

* Accepted to ICLR 2020 

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Why ADAM Beats SGD for Attention Models


Dec 06, 2019
Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J Reddi, Sanjiv Kumar, Suvrit Sra


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Learning to Learn by Zeroth-Order Oracle


Oct 21, 2019
Yangjun Ruan, Yuanhao Xiong, Sashank Reddi, Sanjiv Kumar, Cho-Jui Hsieh


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Online Hierarchical Clustering Approximations


Sep 20, 2019
Aditya Krishna Menon, Anand Rajagopalan, Baris Sumengen, Gui Citovsky, Qin Cao, Sanjiv Kumar

* 17 pages, 3 figures 

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