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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 Koneńćn√Ĺ, 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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New Loss Functions for Fast Maximum Inner Product Search

Sep 11, 2019
Ruiqi Guo, Quan Geng, David Simcha, Felix Chern, Sanjiv Kumar, Xiang Wu


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AdaCliP: Adaptive Clipping for Private SGD

Aug 20, 2019
Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar

* 18 pages 

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Sampled Softmax with Random Fourier Features

Jul 24, 2019
Ankit Singh Rawat, Jiecao Chen, Felix Yu, Ananda Theertha Suresh, Sanjiv Kumar


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Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise

Jun 05, 2019
Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh


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On the Convergence of Adam and Beyond

Apr 19, 2019
Sashank J. Reddi, Satyen Kale, Sanjiv Kumar

* Appeared in ICLR 2018 

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Local Orthogonal Decomposition for Maximum Inner Product Search

Mar 25, 2019
Xiang Wu, Ruiqi Guo, Sanjiv Kumar, David Simcha


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Efficient Inner Product Approximation in Hybrid Spaces

Mar 20, 2019
Xiang Wu, Ruiqi Guo, David Simcha, Dave Dopson, Sanjiv Kumar


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Escaping Saddle Points with Adaptive Gradient Methods

Jan 26, 2019
Matthew Staib, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar, Suvrit Sra


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Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks

Oct 29, 2018
Patrick H. Chen, Si Si, Sanjiv Kumar, Yang Li, Cho-Jui Hsieh


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