Co-regularization Based Semi-supervised Domain Adaptation. - Hal Daumé III; Abhishek Kumar 001; Avishek Saha (NIPS, 2010)

A Co-training Approach for Multi-view Spectral Clustering. - Abhishek Kumar 001; Hal Daumé III (ICML, 2011)

Co-regularized Multi-view Spectral Clustering. - Abhishek Kumar 001; Piyush Rai; Hal Daumé III (NIPS, 2011)

Generalized Multiview Analysis: A discriminative latent space. - Abhishek Sharma 001; Abhishek Kumar 001; Hal Daumé III; David W. Jacobs (CVPR, 2012)

Learning Task Grouping and Overlap in Multi-task Learning. - Abhishek Kumar 001; Hal Daumé III (ICML, 2012)

A Binary Classification Framework for Two-Stage Multiple Kernel Learning. - Abhishek Kumar 001; Alexandru Niculescu-Mizil; Koray Kavukcuoglu; Hal Daumé III (ICML, 2012)

Mixed-Effects Shape Models for Estimating Longitudinal Changes in Anatomy. - Manasi Datar; Prasanna Muralidharan; Abhishek Kumar 001; Sylvain Gouttard; Joseph Piven; Guido Gerig; Ross T. Whitaker; P. Thomas Fletcher (STIA, 2012)

Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression. - Piyush Rai; Abhishek Kumar 001; Hal Daumé III (NIPS, 2012)

Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization. - Abhishek Kumar 001; Vikas Sindhwani; Prabhanjan Kambadur (ICML (1), 2013)

Learning with Multiple Similarities. - Abhishek Kumar 001 (2013)

Near-separable Non-negative Matrix Factorization with ℓ1 and Bregman Loss Functions. - Abhishek Kumar 001; Vikas Sindhwani (SDM, 2015)

Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation. - Ian En-Hsu Yen; Dmitry Malioutov; Abhishek Kumar 001 (AISTATS, 2016)

Large-scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices. - Dmitry Malioutov; Abhishek Kumar 001; Ian En-Hsu Yen (UAI, 2016)

Local Group Invariant Representations via Orbit Embeddings. - Anant Raj; Abhishek Kumar 001; Youssef Mroueh; Tom Fletcher; Bernhard Schölkopf (AISTATS, 2017)

Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification. - Yongxi Lu; Abhishek Kumar 001; Shuangfei Zhai; Yu Cheng 001; Tara Javidi; Rogério Schmidt Feris (CVPR, 2017)

S3Pool: Pooling with Stochastic Spatial Sampling. - Shuangfei Zhai; Hui Wu 009; Abhishek Kumar 001; Yu Cheng 001; Yongxi Lu; Zhongfei Zhang; Rogério Schmidt Feris (CVPR, 2017)

Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference. - Abhishek Kumar 001; Prasanna Sattigeri; Tom Fletcher (NIPS, 2017)

Improved Semi-supervised Learning with GANs using Manifold Invariances. - Abhishek Kumar 001; Prasanna Sattigeri; P. Thomas Fletcher (CoRR, 2017)

Performance of natural language classifiers in a question-answering system. - Raimo Bakis; Daniel P. Connors; Parijat Dube; Pavan Kapanipathi; Abhishek Kumar 001; Dmitry Malioutov; Chitra Venkatramani (IBM J. Res. Dev., 2017)

The Riemannian Geometry of Deep Generative Models. - Hang Shao 004; Abhishek Kumar 001; P. Thomas Fletcher (CVPR Workshops, 2018)

BlockDrop: Dynamic Inference Paths in Residual Networks. - Zuxuan Wu; Tushar Nagarajan; Abhishek Kumar 001; Steven Rennie; Larry S. Davis; Kristen Grauman; Rogério Schmidt Feris (CVPR, 2018)

Variational Inference of Disentangled Latent Concepts from Unlabeled Observations. - Abhishek Kumar 001; Prasanna Sattigeri; Avinash Balakrishnan (ICLR (Poster), 2018)

Co-regularized Alignment for Unsupervised Domain Adaptation. - Abhishek Kumar 001; Prasanna Sattigeri; Kahini Wadhawan; Leonid Karlinsky; Rogério Schmidt Feris; Bill Freeman; Gregory W. Wornell (NeurIPS, 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 001; Rogério Schmidt Feris; Raja Giryes; Alexander M. Bronstein (NeurIPS, 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 001; Raja Giryes; Alexander M. Bronstein (CoRR, 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 001; Samuel Thomas 001; Aleksandra Mojsilovic; Kush R. Varshney (CoRR, 2018)

SpotTune: Transfer Learning Through Adaptive Fine-Tuning. - Yunhui Guo; Honghui Shi; Abhishek Kumar 001; Kristen Grauman; Tajana Rosing; Rogério Schmidt Feris (CVPR, 2019)

Refined α-Divergence Variational Inference via Rejection Sampling. - Rahul Sharma; Abhishek Kumar 001; Piyush Rai (CoRR, 2019)

Nonparametric Bayesian Structure Adaptation for Continual Learning. - Abhishek Kumar 001; Sunabha Chatterjee; Piyush Rai (CoRR, 2019)

Generalized Adversarially Learned Inference. - Yatin Dandi; Homanga Bharadhwaj; Abhishek Kumar 001; Piyush Rai (AAAI, 2021)

Bayesian Structural Adaptation for Continual Learning. - Abhishek Kumar 001; Sunabha Chatterjee; Piyush Rai (ICML, 2021)

DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents. - Kushagra Pandey; Avideep Mukherjee; Piyush Rai; Abhishek Kumar 001 (Trans. Mach. Learn. Res., 2022)

Towards Last-layer Retraining for Group Robustness with Fewer Annotations. - Tyler LaBonte; Vidya Muthukumar; Abhishek Kumar 001 (NeurIPS, 2023)

The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations. - Tyler LaBonte; John C. Hill; Xinchen Zhang; Vidya Muthukumar; Abhishek Kumar 001 (NeurIPS, 2024)