Abhishek Kumar

According to our database, Abhishek Kumar authored at least 34 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations.

Tyler LaBonte, John C. Hill, Xinchen Zhang, Vidya Muthukumar, Abhishek Kumar

CoRR, 2024

2023

Towards Last-layer Retraining for Group Robustness with Fewer Annotations.

Tyler LaBonte, Vidya Muthukumar, Abhishek Kumar

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

2022

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

Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar

Trans. Mach. Learn. Res., 2022

2021

Bayesian Structural Adaptation for Continual Learning.

Abhishek Kumar, Sunabha Chatterjee, Piyush Rai

Proceedings of the 38th International Conference on Machine Learning, 2021

Generalized Adversarially Learned Inference.

Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Nonparametric Bayesian Structure Adaptation for Continual Learning.

Abhishek Kumar, Sunabha Chatterjee, Piyush Rai

CoRR, 2019

Refined α-Divergence Variational Inference via Rejection Sampling.

Rahul Sharma, Abhishek Kumar, Piyush Rai

CoRR, 2019

SpotTune: Transfer Learning Through Adaptive Fine-Tuning.

Yunhui Guo, Honghui Shi, Abhishek Kumar, Kristen Grauman, Tajana Rosing, Rogério Schmidt Feris

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Understanding Unequal Gender Classification Accuracy from Face Images.

Vidya Muthukumar, Tejaswini Pedapati, Nalini K. Ratha, Prasanna Sattigeri, Chai-Wah Wu, Brian Kingsbury, Abhishek Kumar, Samuel Thomas, Aleksandra Mojsilovic, Kush R. Varshney

CoRR, 2018

RepMet: Representative-based metric learning for classification and one-shot object detection.

Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Sharathchandra Pankanti, Rogério Schmidt Feris, Abhishek Kumar, Raja Giryes, Alexander M. Bronstein

CoRR, 2018

Delta-encoder: an effective sample synthesis method for few-shot object recognition.

Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Abhishek Kumar, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein

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

Co-regularized Alignment for Unsupervised Domain Adaptation.

Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan, Leonid Karlinsky, Rogério Schmidt Feris, Bill Freeman, Gregory W. Wornell

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

Variational Inference of Disentangled Latent Concepts from Unlabeled Observations.

Abhishek Kumar, Prasanna Sattigeri, Avinash Balakrishnan

Proceedings of the 6th International Conference on Learning Representations, 2018

BlockDrop: Dynamic Inference Paths in Residual Networks.

Zuxuan Wu, Tushar Nagarajan, Abhishek Kumar, Steven Rennie, Larry S. Davis, Kristen Grauman, Rogério Schmidt Feris

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

The Riemannian Geometry of Deep Generative Models.

Hang Shao, Abhishek Kumar, P. Thomas Fletcher

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

2017

Performance of natural language classifiers in a question-answering system.

Raimo Bakis, Daniel P. Connors, Parijat Dube, Pavan Kapanipathi, Abhishek Kumar, Dmitry Malioutov, Chitra Venkatramani

IBM J. Res. Dev., 2017

Improved Semi-supervised Learning with GANs using Manifold Invariances.

Abhishek Kumar, Prasanna Sattigeri, P. Thomas Fletcher

CoRR, 2017

Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference.

Abhishek Kumar, Prasanna Sattigeri, Tom Fletcher

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

S3Pool: Pooling with Stochastic Spatial Sampling.

Shuangfei Zhai, Hui Wu, Abhishek Kumar, Yu Cheng, Yongxi Lu, Zhongfei Zhang, Rogério Schmidt Feris

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification.

Yongxi Lu, Abhishek Kumar, Shuangfei Zhai, Yu Cheng, Tara Javidi, Rogério Schmidt Feris

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Local Group Invariant Representations via Orbit Embeddings.

Anant Raj, Abhishek Kumar, Youssef Mroueh, Tom Fletcher, Bernhard Schölkopf

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Large-scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices.

Dmitry Malioutov, Abhishek Kumar, Ian En-Hsu Yen

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation.

Ian En-Hsu Yen, Dmitry Malioutov, Abhishek Kumar

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

2015

Near-separable Non-negative Matrix Factorization with ℓ₁ and Bregman Loss Functions.

Abhishek Kumar, Vikas Sindhwani

Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

2013

Learning with Multiple Similarities.

Abhishek Kumar

PhD thesis, 2013

Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization.

Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur

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

2012

Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression.

Piyush Rai, Abhishek Kumar, Hal Daumé III

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Mixed-Effects Shape Models for Estimating Longitudinal Changes in Anatomy.

Manasi Datar, Prasanna Muralidharan, Abhishek Kumar, Sylvain Gouttard, Joseph Piven, Guido Gerig, Ross T. Whitaker, P. Thomas Fletcher

Proceedings of the Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data, 2012

A Binary Classification Framework for Two-Stage Multiple Kernel Learning.

Abhishek Kumar, Alexandru Niculescu-Mizil, Koray Kavukcuoglu, Hal Daumé III

Proceedings of the 29th International Conference on Machine Learning, 2012

Learning Task Grouping and Overlap in Multi-task Learning.

Abhishek Kumar, Hal Daumé III

Proceedings of the 29th International Conference on Machine Learning, 2012

Generalized Multiview Analysis: A discriminative latent space.

Abhishek Sharma, Abhishek Kumar, Hal Daumé III, David W. Jacobs

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

Co-regularized Multi-view Spectral Clustering.

Abhishek Kumar, Piyush Rai, Hal Daumé III

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

A Co-training Approach for Multi-view Spectral Clustering.

Abhishek Kumar, Hal Daumé III

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

Co-regularization Based Semi-supervised Domain Adaptation.

Hal Daumé III, Abhishek Kumar, Avishek Saha

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010