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Kumar Avinava Dubey
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2020 – today
- 2024
[j4]Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Manzil Zaheer, Andrew McCallum, Amr Ahmed, Snigdha Chaturvedi:
Incremental Extractive Opinion Summarization Using Cover Trees. Trans. Mach. Learn. Res. 2024 (2024)- [c37]Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller:
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. AISTATS 2024: 2278-2286 - [c36]Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami, Rahul Kidambi, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests. ICLR 2024 - [c35]Arijit Sehanobish, Krzysztof Marcin Choromanski, Yunfan Zhao, Kumar Avinava Dubey, Valerii Likhosherstov:
Scalable Neural Network Kernels. ICLR 2024 - [c34]Isabel Leal, Krzysztof Choromanski, Deepali Jain, Avinava Dubey, Jake Varley, Michael S. Ryoo, Yao Lu, Frederick Liu, Vikas Sindhwani, Quan Vuong, Tamás Sarlós, Ken Oslund, Karol Hausman, Kanishka Rao:
SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. ICRA 2024: 6920-6927 - [c33]Avinava Dubey
, Zhe Feng, Rahul Kidambi, Aranyak Mehta, Di Wang:
Auctions with LLM Summaries. KDD 2024: 713-722 - [i31]Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Manzil Zaheer, Andrew McCallum, Amr Ahmed, Snigdha Chaturvedi:
Incremental Extractive Opinion Summarization Using Cover Trees. CoRR abs/2401.08047 (2024) - [i30]Jake Varley, Sumeet Singh, Deepali Jain, Krzysztof Choromanski, Andy Zeng, Somnath Basu Roy Chowdhury, Avinava Dubey, Vikas Sindhwani:
Embodied AI with Two Arms: Zero-shot Learning, Safety and Modularity. CoRR abs/2404.03570 (2024) - [i29]Kumar Avinava Dubey, Zhe Feng, Rahul Kidambi, Aranyak Mehta, Di Wang:
Auctions with LLM Summaries. CoRR abs/2404.08126 (2024) - [i28]Krzysztof Choromanski, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Han Lin, Avinava Dubey, Tamás Sarlós, Snigdha Chaturvedi:
Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers. CoRR abs/2406.15881 (2024) - [i27]Somnath Basu Roy Chowdhury, Krzysztof Choromanski, Arijit Sehanobish, Avinava Dubey, Snigdha Chaturvedi:
Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning. CoRR abs/2406.16257 (2024) - [i26]Arijit Sehanobish, Avinava Dubey, Krzysztof Choromanski, Somnath Basu Roy Chowdhury, Deepali Jain, Vikas Sindhwani, Snigdha Chaturvedi:
Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning. CoRR abs/2406.17740 (2024) - [i25]Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Avinava Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent:
Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning. CoRR abs/2407.15762 (2024) - 2023
- [c32]Brianna Zitkovich, Tianhe Yu, Sichun Xu, Peng Xu, Ted Xiao, Fei Xia, Jialin Wu, Paul Wohlhart, Stefan Welker, Ayzaan Wahid, Quan Vuong, Vincent Vanhoucke, Huong T. Tran, Radu Soricut, Anikait Singh, Jaspiar Singh, Pierre Sermanet, Pannag R. Sanketi, Grecia Salazar, Michael S. Ryoo, Krista Reymann, Kanishka Rao, Karl Pertsch, Igor Mordatch, Henryk Michalewski, Yao Lu, Sergey Levine, Lisa Lee, Tsang-Wei Edward Lee, Isabel Leal, Yuheng Kuang, Dmitry Kalashnikov, Ryan Julian, Nikhil J. Joshi, Alex Irpan, Brian Ichter, Jasmine Hsu, Alexander Herzog, Karol Hausman, Keerthana Gopalakrishnan, Chuyuan Fu, Pete Florence, Chelsea Finn, Kumar Avinava Dubey, Danny Driess, Tianli Ding, Krzysztof Marcin Choromanski, Xi Chen, Yevgen Chebotar, Justice Carbajal, Noah Brown, Anthony Brohan, Montserrat Gonzalez Arenas, Kehang Han:
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRL 2023: 2165-2183 - [c31]Krzysztof Marcin Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Kumar Avinava Dubey, Deepali Jain, Tamás Sarlós, Snigdha Chaturvedi, Adrian Weller:
Efficient Graph Field Integrators Meet Point Clouds. ICML 2023: 5978-6004 - [c30]Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Robust Concept Erasure via Kernelized Rate-Distortion Maximization. NeurIPS 2023 - [c29]Deepali Jain, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan:
Mnemosyne: Learning to Train Transformers with Transformers. NeurIPS 2023 - [c28]Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel. NeurIPS 2023 - [i24]Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features. CoRR abs/2302.00787 (2023) - [i23]Krzysztof Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Avinava Dubey, Deepali Jain, Tamás Sarlós, Snigdha Chaturvedi, Adrian Weller:
Efficient Graph Field Integrators Meet Point Clouds. CoRR abs/2302.00942 (2023) - [i22]Deepali Jain, Krzysztof Marcin Choromanski, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan, Avinava Dubey:
Mnemosyne: Learning to Train Transformers with Transformers. CoRR abs/2302.01128 (2023) - [i21]Krzysztof Marcin Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller:
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. CoRR abs/2302.01925 (2023) - [i20]Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Xi Chen, Krzysztof Choromanski, Tianli Ding, Danny Driess, Avinava Dubey, Chelsea Finn, Pete Florence, Chuyuan Fu, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Kehang Han, Karol Hausman, Alexander Herzog, Jasmine Hsu, Brian Ichter, Alex Irpan, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Lisa Lee, Tsang-Wei Edward Lee, Sergey Levine, Yao Lu, Henryk Michalewski, Igor Mordatch, Karl Pertsch, Kanishka Rao, Krista Reymann, Michael S. Ryoo, Grecia Salazar, Pannag Sanketi, Pierre Sermanet, Jaspiar Singh, Anikait Singh, Radu Soricut, Huong T. Tran, Vincent Vanhoucke, Quan Vuong, Ayzaan Wahid, Stefan Welker, Paul Wohlhart, Jialin Wu, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich:
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRR abs/2307.15818 (2023) - [i19]Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami, Rahul Kidambi, Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests. CoRR abs/2310.11401 (2023) - [i18]Arijit Sehanobish, Krzysztof Choromanski, Yunfan Zhao, Avinava Dubey, Valerii Likhosherstov:
Scalable Neural Network Kernels. CoRR abs/2310.13225 (2023) - [i17]Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Robust Concept Erasure via Kernelized Rate-Distortion Maximization. CoRR abs/2312.00194 (2023) - [i16]Isabel Leal, Krzysztof Choromanski, Deepali Jain, Avinava Dubey, Jake Varley, Michael S. Ryoo, Yao Lu, Frederick Liu, Vikas Sindhwani, Quan Vuong, Tamás Sarlós, Ken Oslund, Karol Hausman, Kanishka Rao:
SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. CoRR abs/2312.01990 (2023) - 2022
- [j3]Sankalan Pal Chowdhury, Adamos Solomou, Kumar Avinava Dubey, Mrinmaya Sachan:
Learning the Transformer Kernel. Trans. Mach. Learn. Res. 2022 (2022) - [c27]Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
Chefs' Random Tables: Non-Trigonometric Random Features. NeurIPS 2022 - [c26]Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Kumar Avinava Dubey, Manzil Zaheer:
A Fourier Approach to Mixture Learning. NeurIPS 2022 - [i15]Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
Chefs' Random Tables: Non-Trigonometric Random Features. CoRR abs/2205.15317 (2022) - [i14]Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Unsupervised Opinion Summarization Using Approximate Geodesics. CoRR abs/2209.07496 (2022) - [i13]Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Avinava Dubey, Manzil Zaheer:
A Fourier Approach to Mixture Learning. CoRR abs/2210.02415 (2022) - [i12]Zahra Shamsi, Drew Bryant, Jacob Wilson, Xiaoyu Qu, Avinava Dubey, Konik Kothari, Mostafa Dehghani, Mariya Chavarha, Valerii Likhosherstov, Brian Williams, Michael Frumkin, Fred Appelbaum, Krzysztof Choromanski, Ali Bashir, Min Fang:
Automated Deep Aberration Detection from Chromosome Karyotype Images. CoRR abs/2211.14312 (2022) - 2021
- [c25]Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey, Amr Ahmed, Andrew McCallum:
DAG-Structured Clustering by Nearest Neighbors. AISTATS 2021: 2854-2862 - [c24]Nicholas Monath, Kumar Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu:
Scalable Hierarchical Agglomerative Clustering. KDD 2021: 1245-1255 - [c23]Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum:
Exact and approximate hierarchical clustering using A. UAI 2021: 2061-2071 - [i11]Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum:
Exact and Approximate Hierarchical Clustering Using A. CoRR abs/2104.07061 (2021) - [i10]Sankalan Pal Chowdhury, Adamos Solomou, Avinava Dubey, Mrinmaya Sachan:
On Learning the Transformer Kernel. CoRR abs/2110.08323 (2021) - 2020
- [j2]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
Contextual Explanation Networks. J. Mach. Learn. Res. 21: 194:1-194:44 (2020) - [c22]Kumar Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead Williamson:
Distributed, partially collapsed MCMC for Bayesian Nonparametrics. AISTATS 2020: 3685-3695 - [c21]Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontañón, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed:
Big Bird: Transformers for Longer Sequences. NeurIPS 2020 - [i9]Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead A. Williamson:
Distributed, partially collapsed MCMC for Bayesian Nonparametrics. CoRR abs/2001.05591 (2020) - [i8]Manzil Zaheer, Guru Guruganesh, Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontañón, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed:
Big Bird: Transformers for Longer Sequences. CoRR abs/2007.14062 (2020) - [i7]Nicholas Monath, Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu:
Scalable Bottom-Up Hierarchical Clustering. CoRR abs/2010.11821 (2020)
2010 – 2019
- 2019
- [j1]Mrinmaya Sachan, Avinava Dubey, Eduard H. Hovy, Tom M. Mitchell, Dan Roth, Eric P. Xing:
Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks. Comput. Linguistics 45(4): 627-665 (2019) - 2018
- [c20]Junier B. Oliva, Avinava Dubey, Manzil Zaheer, Barnabás Póczos, Ruslan Salakhutdinov, Eric P. Xing, Jeff Schneider:
Transformation Autoregressive Networks. ICML 2018: 3895-3904 - [c19]Mrinmaya Sachan, Kumar Avinava Dubey, Tom M. Mitchell, Dan Roth, Eric P. Xing:
Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems. NeurIPS 2018: 140-151 - [i6]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
The Intriguing Properties of Model Explanations. CoRR abs/1801.09808 (2018) - [i5]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
Personalized Survival Prediction with Contextual Explanation Networks. CoRR abs/1801.09810 (2018) - [i4]Mrinmaya Sachan, Kumar Avinava Dubey, Eduard H. Hovy, Tom M. Mitchell, Dan Roth, Eric P. Xing:
Discourse in Multimedia: A Case Study in Information Extraction. CoRR abs/1811.05546 (2018) - 2017
- [c18]Mrinmaya Sachan, Avinava Dubey, Eric P. Xing:
From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems. EMNLP 2017: 773-784 - [i3]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
Contextual Explanation Networks. CoRR abs/1705.10301 (2017) - [i2]Junier B. Oliva, Kumar Avinava Dubey, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider:
Recurrent Estimation of Distributions. CoRR abs/1705.10750 (2017) - 2016
- [c17]Mrinmaya Sachan, Kumar Avinava Dubey, Eric P. Xing:
Science Question Answering using Instructional Materials. ACL (2) 2016 - [c16]Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing:
Bayesian Nonparametric Kernel-Learning. AISTATS 2016: 1078-1086 - [c15]Emmanouil Antonios Platanios, Avinava Dubey, Tom M. Mitchell:
Estimating Accuracy from Unlabeled Data: A Bayesian Approach. ICML 2016: 1416-1425 - [c14]Kumar Avinava Dubey, Sashank J. Reddi, Sinead A. Williamson, Barnabás Póczos, Alexander J. Smola, Eric P. Xing:
Variance Reduction in Stochastic Gradient Langevin Dynamics. NIPS 2016: 1154-1162 - [i1]Mrinmaya Sachan, Avinava Dubey, Eric P. Xing:
Science Question Answering using Instructional Materials. CoRR abs/1602.04375 (2016) - 2015
- [c13]Mrinmaya Sachan, Kumar Avinava Dubey, Eric P. Xing, Matthew Richardson:
Learning Answer-Entailing Structures for Machine Comprehension. ACL (1) 2015: 239-249 - [c12]Zhiting Hu, Qirong Ho, Avinava Dubey, Eric P. Xing:
Large-scale Distributed Dependent Nonparametric Trees. ICML 2015: 1651-1659 - [c11]Sashank J. Reddi, Ahmed Hefny, Carlton Downey, Avinava Dubey, Suvrit Sra:
Large-scale randomized-coordinate descent methods with non-separable linear constraints. UAI 2015: 762-771 - 2014
- [c10]Kumar Avinava Dubey, Qirong Ho, Sinead A. Williamson, Eric P. Xing:
Dependent nonparametric trees for dynamic hierarchical clustering. NIPS 2014: 1152-1160 - [c9]Kumar Avinava Dubey, Sinead Williamson, Eric P. Xing:
Parallel Markov Chain Monte Carlo for Pitman-Yor Mixture Models. UAI 2014: 142-151 - [c8]Mrinmaya Sachan, Avinava Dubey, Shashank Srivastava, Eric P. Xing, Eduard H. Hovy:
Spatial compactness meets topical consistency: jointly modeling links and content for community detection. WSDM 2014: 503-512 - 2013
- [c7]Sinead Williamson, Avinava Dubey, Eric P. Xing:
Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models. ICML (1) 2013: 98-106 - [c6]Avinava Dubey, Ahmed Hefny, Sinead Williamson, Eric P. Xing:
A Nonparametric Mixture Model for Topic Modeling over Time. SDM 2013: 530-538 - 2012
- [c5]Senthil Mani, Rose Catherine, Vibha Singhal Sinha, Avinava Dubey:
AUSUM: approach for unsupervised bug report summarization. SIGSOFT FSE 2012: 11 - 2011
- [c4]Avinava Dubey, Indrajit Bhattacharya, Mrinal Kanti Das, Tanveer A. Faruquie, Chiranjib Bhattacharyya:
Learning Dirichlet Processes from Partially Observed Groups. ICDM 2011: 141-150 - [c3]Avinava Dubey, Soumen Chakrabarti, Chiranjib Bhattacharyya:
Diversity in ranking via resistive graph centers. KDD 2011: 78-86 - 2010
- [c2]Avinava Dubey, Indrajit Bhattacharya, Shantanu Godbole:
A Cluster-Level Semi-supervision Model for Interactive Clustering. ECML/PKDD (1) 2010: 409-424
2000 – 2009
- 2009
- [c1]Avinava Dubey, Jinesh Machchhar, Chiranjib Bhattacharyya, Soumen Chakrabarti:
Conditional Models for Non-smooth Ranking Loss Functions. ICDM 2009: 129-138
Coauthor Index
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