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To Aggregate or Not? Learning with Separate Noisy Labels



Jiaheng Wei , Zhaowei Zhu , Tianyi Luo , Ehsan Amid , Abhishek Kumar , Yang Liu

* Paper under Review 

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GridShift: A Faster Mode-seeking Algorithm for Image Segmentation and Object Tracking



Abhishek Kumar , Oladayo S. Ajani , Swagatam Das , Rammohan Mallipeddi


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DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents



Kushagra Pandey , Avideep Mukherjee , Piyush Rai , Abhishek Kumar


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Solving Inverse Problems with NerfGANs



Giannis Daras , Wen-Sheng Chu , Abhishek Kumar , Dmitry Lagun , Alexandros G. Dimakis

* 16 pages, 18 figures 

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When Creators Meet the Metaverse: A Survey on Computational Arts



Lik-Hang Lee , Zijun Lin , Rui Hu , Zhengya Gong , Abhishek Kumar , Tangyao Li , Sijia Li , Pan Hui

* Submitted to ACM Computing Surveys, 36 pages 

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Constrained Instance and Class Reweighting for Robust Learning under Label Noise



Abhishek Kumar , Ehsan Amid

* 27 pages, including Appendix 

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Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications



Young D. Kwon , Jagmohan Chauhan , Abhishek Kumar , Pan Hui , Cecilia Mascolo

* Accepted for publication at SEC 2021 

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Implicit Rate-Constrained Optimization of Non-decomposable Objectives



Abhishek Kumar , Harikrishna Narasimhan , Andrew Cotter

* ICML 2021; Code available at https://github.com/google-research/google-research/tree/master/implicit_constrained_optimization 

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Wavelet Design in a Learning Framework



Dhruv Jawali , Abhishek Kumar , Chandra Sekhar Seelamantula

* This work has been submitted to the IEEE Transactions on Pattern Analysis and Machine Intelligence for possible publication 

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