Avinava Dubey

According to our database, Avinava Dubey authored at least 57 papers between 2009 and 2024.

Collaborative distances:

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2024

Incremental Extractive Opinion Summarization Using Cover Trees.

Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Manzil Zaheer, Andrew McCallum, Amr Ahmed, Snigdha Chaturvedi

Trans. Mach. Learn. Res., 2024

Optimal Time Complexity Algorithms for Computing General Random Walk Graph Kernels on Sparse Graphs.

Krzysztof Choromanski, Isaac Reid, Arijit Sehanobish, Avinava Dubey

CoRR, 2024

Magnituder Layers for Implicit Neural Representations in 3D.

Sang Min Kim, Byeongchan Kim, Arijit Sehanobish, Krzysztof Choromanski, Dongseok Shim, Avinava Dubey, Min-hwan Oh

CoRR, 2024

Linear Transformer Topological Masking with Graph Random Features.

Isaac Reid, Kumar Avinava Dubey, Deepali Jain, Will Whitney, Amr Ahmed, Joshua Ainslie, Alex Bewley, Mithun George Jacob, Aranyak Mehta, David Rendleman, Connor Schenck, Richard E. Turner, René Wagner, Adrian Weller, Krzysztof Choromanski

CoRR, 2024

Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning.

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

CoRR, 2024

Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning.

Arijit Sehanobish, Avinava Dubey, Krzysztof Choromanski, Somnath Basu Roy Chowdhury, Deepali Jain, Vikas Sindhwani, Snigdha Chaturvedi

CoRR, 2024

Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning.

Somnath Basu Roy Chowdhury, Krzysztof Choromanski, Arijit Sehanobish, Avinava Dubey, Snigdha Chaturvedi

CoRR, 2024

Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers.

Krzysztof Choromanski, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Han Lin, Avinava Dubey, Tamás Sarlós, Snigdha Chaturvedi

CoRR, 2024

Embodied AI with Two Arms: Zero-shot Learning, Safety and Modularity.

Jake Varley, Sumeet Singh, Deepali Jain, Krzysztof Choromanski, Andy Zeng, Somnath Basu Roy Chowdhury, Avinava Dubey, Vikas Sindhwani

CoRR, 2024

Auctions with LLM Summaries.

Avinava Dubey, Zhe Feng, Rahul Kidambi, Aranyak Mehta, Di Wang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention.

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

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Scalable Neural Network Kernels.

Arijit Sehanobish, Krzysztof Marcin Choromanski, Yunfan Zhao, Kumar Avinava Dubey, Valerii Likhosherstov

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Enhancing Group Fairness in Online Settings Using Oblique Decision Forests.

Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami, Rahul Kidambi, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers.

Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features.

Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller

CoRR, 2023

Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel.

Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mnemosyne: Learning to Train Transformers with Transformers.

Deepali Jain, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Robust Concept Erasure via Kernelized Rate-Distortion Maximization.

Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Graph Field Integrators Meet Point Clouds.

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

Proceedings of the International Conference on Machine Learning, 2023

Unsupervised Opinion Summarization Using Approximate Geodesics.

Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

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

Proceedings of the Conference on Robot Learning, 2023

2022

Learning the Transformer Kernel.

Sankalan Pal Chowdhury, Adamos Solomou, Kumar Avinava Dubey, Mrinmaya Sachan

Trans. Mach. Learn. Res., 2022

Automated Deep Aberration Detection from Chromosome Karyotype Images.

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

CoRR, 2022

A Fourier Approach to Mixture Learning.

Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Kumar Avinava Dubey, Manzil Zaheer

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Chefs' Random Tables: Non-Trigonometric Random Features.

Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Exact and approximate hierarchical clustering using A.

Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Scalable Hierarchical Agglomerative Clustering.

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

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

DAG-Structured Clustering by Nearest Neighbors.

Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey, Amr Ahmed, Andrew McCallum

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Contextual Explanation Networks.

Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing

J. Mach. Learn. Res., 2020

Scalable Bottom-Up Hierarchical Clustering.

Nicholas Monath, Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu

CoRR, 2020

Big Bird: Transformers for Longer Sequences.

Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontañón, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Distributed, partially collapsed MCMC for Bayesian Nonparametrics.

Kumar Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead Williamson

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks.

Mrinmaya Sachan, Avinava Dubey, Eduard H. Hovy, Tom M. Mitchell, Dan Roth, Eric P. Xing

Comput. Linguistics, 2019

2018

Discourse in Multimedia: A Case Study in Information Extraction.

Mrinmaya Sachan, Kumar Avinava Dubey, Eduard H. Hovy, Tom M. Mitchell, Dan Roth, Eric P. Xing

CoRR, 2018

Personalized Survival Prediction with Contextual Explanation Networks.

Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing

CoRR, 2018

The Intriguing Properties of Model Explanations.

Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing

CoRR, 2018

Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems.

Mrinmaya Sachan, Kumar Avinava Dubey, Tom M. Mitchell, Dan Roth, Eric P. Xing

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Transformation Autoregressive Networks.

Junier B. Oliva, Avinava Dubey, Manzil Zaheer, Barnabás Póczos, Ruslan Salakhutdinov, Eric P. Xing, Jeff Schneider

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Recurrent Estimation of Distributions.

Junier B. Oliva, Kumar Avinava Dubey, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider

CoRR, 2017

From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems.

Mrinmaya Sachan, Avinava Dubey, Eric P. Xing

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

2016

Variance Reduction in Stochastic Gradient Langevin Dynamics.

Kumar Avinava Dubey, Sashank J. Reddi, Sinead A. Williamson, Barnabás Póczos, Alexander J. Smola, Eric P. Xing

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Estimating Accuracy from Unlabeled Data: A Bayesian Approach.

Emmanouil Antonios Platanios, Avinava Dubey, Tom M. Mitchell

Proceedings of the 33nd International Conference on Machine Learning, 2016

Bayesian Nonparametric Kernel-Learning.

Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Science Question Answering using Instructional Materials.

Mrinmaya Sachan, Kumar Avinava Dubey, Eric P. Xing

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015

Large-scale randomized-coordinate descent methods with non-separable linear constraints.

Sashank J. Reddi, Ahmed Hefny, Carlton Downey, Avinava Dubey, Suvrit Sra

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Large-scale Distributed Dependent Nonparametric Trees.

Zhiting Hu, Qirong Ho, Avinava Dubey, Eric P. Xing

Proceedings of the 32nd International Conference on Machine Learning, 2015

Learning Answer-Entailing Structures for Machine Comprehension.

Mrinmaya Sachan, Kumar Avinava Dubey, Eric P. Xing, Matthew Richardson

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015

2014

Spatial compactness meets topical consistency: jointly modeling links and content for community detection.

Mrinmaya Sachan, Avinava Dubey, Shashank Srivastava, Eric P. Xing, Eduard H. Hovy

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Parallel Markov Chain Monte Carlo for Pitman-Yor Mixture Models.

Kumar Avinava Dubey, Sinead Williamson, Eric P. Xing

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Dependent nonparametric trees for dynamic hierarchical clustering.

Kumar Avinava Dubey, Qirong Ho, Sinead A. Williamson, Eric P. Xing

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

A Nonparametric Mixture Model for Topic Modeling over Time.

Avinava Dubey, Ahmed Hefny, Sinead Williamson, Eric P. Xing

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models.

Sinead Williamson, Avinava Dubey, Eric P. Xing

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

AUSUM: approach for unsupervised bug report summarization.

Senthil Mani, Rose Catherine, Vibha Singhal Sinha, Avinava Dubey

Proceedings of the 20th ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE-20), 2012

2011

Diversity in ranking via resistive graph centers.

Avinava Dubey, Soumen Chakrabarti, Chiranjib Bhattacharyya

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Learning Dirichlet Processes from Partially Observed Groups.

Avinava Dubey, Indrajit Bhattacharya, Mrinal Kanti Das, Tanveer A. Faruquie, Chiranjib Bhattacharyya

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010

A Cluster-Level Semi-supervision Model for Interactive Clustering.

Avinava Dubey, Indrajit Bhattacharya, Shantanu Godbole

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009

Conditional Models for Non-smooth Ranking Loss Functions.

Avinava Dubey, Jinesh Machchhar, Chiranjib Bhattacharyya, Soumen Chakrabarti

Proceedings of the ICDM 2009, 2009