Abhishek Kumar

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 36

Top Venues

CoRR

CVPR

NeurIPS

AISTATS

University of Maryland, College Park, MD, USA (PHD)

Education History

University of Maryland, College Park, MD, USA

PHD

Publications

Tyler LaBonte, John C. Hill, Xinchen Zhang, Vidya Muthukumar, Abhishek Kumar
The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations. CoRR (2024)
Tyler LaBonte, Vidya Muthukumar, Abhishek Kumar
Towards Last-layer Retraining for Group Robustness with Fewer Annotations. NeurIPS (2023)
Tyler LaBonte, Vidya Muthukumar, Abhishek Kumar
Towards Last-layer Retraining for Group Robustness with Fewer Annotations. CoRR (2023)
Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar
DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents. CoRR (2022)
Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar
DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents. Trans. Mach. Learn. Res. 2022 (2022)
Abhishek Kumar, Sunabha Chatterjee, Piyush Rai
Bayesian Structural Adaptation for Continual Learning. ICML (2021)
Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai
Generalized Adversarially Learned Inference. AAAI (2021)
Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai
Generalized Adversarially Learned Inference. CoRR (2020)
Abhishek Kumar, Sunabha Chatterjee, Piyush Rai
Nonparametric Bayesian Structure Adaptation for Continual Learning. CoRR (2019)
Yunhui Guo, Honghui Shi, Abhishek Kumar, Kristen Grauman, Tajana Rosing, Rogério Schmidt Feris
SpotTune: Transfer Learning Through Adaptive Fine-Tuning. CVPR (2019)
Rahul Sharma, Abhishek Kumar, Piyush Rai
Refined α-Divergence Variational Inference via Rejection Sampling. CoRR (2019)
Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Sharathchandra Pankanti, Rogério Schmidt Feris, Abhishek Kumar, Raja Giryes, Alexander M. Bronstein
RepMet: Representative-based metric learning for classification and one-shot object detection. CoRR (2018)
Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan, Leonid Karlinsky, Rogério Schmidt Feris, William T. Freeman, Gregory W. Wornell
Co-regularized Alignment for Unsupervised Domain Adaptation. CoRR (2018)
Hang Shao, Abhishek Kumar, P. Thomas Fletcher
The Riemannian Geometry of Deep Generative Models. CVPR Workshops (2018)
Yunhui Guo, Honghui Shi, Abhishek Kumar, Kristen Grauman, Tajana Rosing, Rogério Schmidt Feris
SpotTune: Transfer Learning through Adaptive Fine-tuning. CoRR (2018)
Zuxuan Wu, Tushar Nagarajan, Abhishek Kumar, Steven Rennie, Larry S. Davis, Kristen Grauman, Rogério Schmidt Feris
BlockDrop: Dynamic Inference Paths in Residual Networks. CVPR (2018)
Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Abhishek Kumar, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein
Delta-encoder: an effective sample synthesis method for few-shot object recognition. NeurIPS (2018)
Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan, Leonid Karlinsky, Rogério Schmidt Feris, Bill Freeman, Gregory W. Wornell
Co-regularized Alignment for Unsupervised Domain Adaptation. NeurIPS (2018)
Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Rogério Schmidt Feris, Abhishek Kumar, Raja Giryes, Alexander M. Bronstein
Delta-encoder: an effective sample synthesis method for few-shot object recognition. CoRR (2018)
Abhishek Kumar, Prasanna Sattigeri, Avinash Balakrishnan
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations. ICLR (Poster) (2018)
Vidya Muthukumar, Tejaswini Pedapati, Nalini K. Ratha, Prasanna Sattigeri, Chai-Wah Wu, Brian Kingsbury, Abhishek Kumar, Samuel Thomas, Aleksandra Mojsilovic, Kush R. Varshney
Understanding Unequal Gender Classification Accuracy from Face Images. CoRR (2018)
Abhishek Kumar, Prasanna Sattigeri, P. Thomas Fletcher
Improved Semi-supervised Learning with GANs using Manifold Invariances. CoRR (2017)
Abhishek Kumar, Prasanna Sattigeri, Avinash Balakrishnan
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations. CoRR (2017)
Hang Shao, Abhishek Kumar, P. Thomas Fletcher
The Riemannian Geometry of Deep Generative Models. CoRR (2017)
Abhishek Kumar, Prasanna Sattigeri, Tom Fletcher
Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference. NIPS (2017)
Shuangfei Zhai, Hui Wu, Abhishek Kumar, Yu Cheng, Yongxi Lu, Zhongfei Zhang, Rogério Schmidt Feris
S3Pool: Pooling with Stochastic Spatial Sampling. CVPR (2017)
Yongxi Lu, Abhishek Kumar, Shuangfei Zhai, Yu Cheng, Tara Javidi, Rogério Schmidt Feris
Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification. CVPR (2017)
Zuxuan Wu, Tushar Nagarajan, Abhishek Kumar, Steven Rennie, Larry S. Davis, Kristen Grauman, Rogério Schmidt Feris
BlockDrop: Dynamic Inference Paths in Residual Networks. CoRR (2017)
Anant Raj, Abhishek Kumar, Youssef Mroueh, Tom Fletcher, Bernhard Schölkopf
Local Group Invariant Representations via Orbit Embeddings. AISTATS (2017)
Raimo Bakis, Daniel P. Connors, Parijat Dube, Pavan Kapanipathi, Abhishek Kumar, Dmitry Malioutov, Chitra Venkatramani
Performance of natural language classifiers in a question-answering system. IBM J. Res. Dev. 61 (4-5) (2017)
Shuangfei Zhai, Hui Wu, Abhishek Kumar, Yu Cheng, Yongxi Lu, Zhongfei Zhang, Rogério Schmidt Feris
S3Pool: Pooling with Stochastic Spatial Sampling. CoRR (2016)
Yongxi Lu, Abhishek Kumar, Shuangfei Zhai, Yu Cheng, Tara Javidi, Rogério Schmidt Feris
Fully-adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification. CoRR (2016)
Dmitry Malioutov, Abhishek Kumar, Ian En-Hsu Yen
Large-scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices. UAI (2016)
Ian En-Hsu Yen, Dmitry Malioutov, Abhishek Kumar
Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation. AISTATS (2016)
Anant Raj, Abhishek Kumar, Youssef Mroueh, P. Thomas Fletcher, Bernhard Schölkopf
Local Group Invariant Representations via Orbit Embeddings. CoRR (2016)
Abhishek Kumar, Vikas Sindhwani
and Bregman Loss Functions. SDM (2015)
Abhishek Kumar, Vikas Sindhwani
- and Bregman Loss Functions. CoRR (2013)
Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur
Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization. ICML (1) (2013)
Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur
Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization CoRR (2012)
Abhishek Kumar, Hal Daumé III
Learning Task Grouping and Overlap in Multi-task Learning. ICML (2012)
Abhishek Sharma, Abhishek Kumar, Hal Daumé III, David W. Jacobs
Generalized Multiview Analysis: A discriminative latent space. CVPR (2012)
Abhishek Kumar, Alexandru Niculescu-Mizil, Koray Kavukcuoglu, Hal Daumé III
A Binary Classification Framework for Two-Stage Multiple Kernel Learning. ICML (2012)
Manasi Datar, Prasanna Muralidharan, Abhishek Kumar, Sylvain Gouttard, Joseph Piven, Guido Gerig, Ross T. Whitaker, P. Thomas Fletcher
Mixed-Effects Shape Models for Estimating Longitudinal Changes in Anatomy. STIA (2012)
Piyush Rai, Abhishek Kumar, Hal Daumé III
Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression. NIPS (2012)
Abhishek Kumar, Piyush Rai, Hal Daumé III
Co-regularized Multi-view Spectral Clustering. NIPS (2011)
Abhishek Kumar, Hal Daumé III
A Co-training Approach for Multi-view Spectral Clustering. ICML (2011)
Hal Daumé III, Abhishek Kumar, Avishek Saha
Co-regularization Based Semi-supervised Domain Adaptation. NIPS (2010)

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Publication Activity (10 Years)

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Abhishek Kumar