Avinava Dubey

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 31

Top Topics

Hierarchical Clustering

Exact And Approximate

Top Venues

Publications

Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Manzil Zaheer, Andrew McCallum, Amr Ahmed, Snigdha Chaturvedi
Incremental Extractive Opinion Summarization Using Cover Trees. CoRR (2024)
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 (2023)
Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi
Robust Concept Erasure via Kernelized Rate-Distortion Maximization. CoRR (2023)
Deepali Jain, Krzysztof Marcin Choromanski, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan, Avinava Dubey
Mnemosyne: Learning to Train Transformers with Transformers. CoRR (2023)
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 (2023)
Arijit Sehanobish, Krzysztof Choromanski, Yunfan Zhao, Avinava Dubey, Valerii Likhosherstov
Scalable Neural Network Kernels. CoRR (2023)
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 (2023)
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 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 (2023)
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 (2023)
Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
Chefs' Random Tables: Non-Trigonometric Random Features. CoRR (2022)
Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi
Unsupervised Opinion Summarization Using Approximate Geodesics. CoRR (2022)
Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Avinava Dubey, Manzil Zaheer
A Fourier Approach to Mixture Learning. CoRR (2022)
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 (2022)
Sankalan Pal Chowdhury, Adamos Solomou, Avinava Dubey, Mrinmaya Sachan
On Learning the Transformer Kernel. CoRR (2021)
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)
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 (2021)
Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing
Contextual Explanation Networks. J. Mach. Learn. Res. 21 (2020)
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 (2020)
Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead A. Williamson
Distributed, partially collapsed MCMC for Bayesian Nonparametrics. CoRR (2020)
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 (2020)
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) (2019)
Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing
The Intriguing Properties of Model Explanations. CoRR (2018)
Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing
Personalized Survival Prediction with Contextual Explanation Networks. CoRR (2018)
Junier B. Oliva, Avinava Dubey, Manzil Zaheer, Barnabás Póczos, Ruslan Salakhutdinov, Eric P. Xing, Jeff Schneider
Transformation Autoregressive Networks. ICML (2018)
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)
Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing
Contextual Explanation Networks. CoRR (2017)
Emmanouil Antonios Platanios, Avinava Dubey, Tom M. Mitchell
Estimating Accuracy from Unlabeled Data: A Bayesian Approach. ICML (2016)
Mrinmaya Sachan, Avinava Dubey, Eric P. Xing
Science Question Answering using Instructional Materials. CoRR (2016)
Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
Bayesian Nonparametric Kernel-Learning. AISTATS (2016)
Zhiting Hu, Qirong Ho, Avinava Dubey, Eric P. Xing
Large-scale Distributed Dependent Nonparametric Trees. ICML (2015)
Sashank J. Reddi, Ahmed Hefny, Carlton Downey, Avinava Dubey, Suvrit Sra
Large-scale randomized-coordinate descent methods with non-separable linear constraints. UAI (2015)
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)
Avinava Dubey, Ahmed Hefny, Sinead Williamson, Eric P. Xing
A Nonparametric Mixture Model for Topic Modeling over Time. SDM (2013)
Sinead Williamson, Avinava Dubey, Eric P. Xing
Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models. ICML (1) (2013)
Senthil Mani, Rose Catherine, Vibha Singhal Sinha, Avinava Dubey
AUSUM: approach for unsupervised bug report summarization. SIGSOFT FSE (2012)
Avinava Dubey, Soumen Chakrabarti, Chiranjib Bhattacharyya
Diversity in ranking via resistive graph centers. KDD (2011)
Avinava Dubey, Indrajit Bhattacharya, Mrinal Kanti Das, Tanveer A. Faruquie, Chiranjib Bhattacharyya
Learning Dirichlet Processes from Partially Observed Groups. ICDM (2011)
Avinava Dubey, Indrajit Bhattacharya, Shantanu Godbole
A Cluster-Level Semi-supervision Model for Interactive Clustering. ECML/PKDD (1) (2010)
Avinava Dubey, Jinesh Machchhar, Chiranjib Bhattacharyya, Soumen Chakrabarti
Conditional Models for Non-smooth Ranking Loss Functions. ICDM (2009)