A Projection Free Method for Generalized Eigenvalue Problem with a Nonsmooth Regularizer. - Seong Jae Hwang; Maxwell D. Collins; Sathya N. Ravi; Vamsi K. Ithapu; Nagesh Adluru; Sterling C. Johnson; Vikas Singh (ICCV, 2015)

On Statistical Analysis of Neuroimages with Imperfect Registration. - Won Hwa Kim; Sathya N. Ravi; Sterling C. Johnson; Ozioma C. Okonkwo; Vikas Singh (ICCV, 2015)

An NMF Perspective on Binary Hashing. - Lopamudra Mukherjee; Sathya N. Ravi; Vamsi K. Ithapu; Tyler Holmes; Vikas Singh (ICCV, 2015)

Convergence of gradient based pre-training in Denoising autoencoders. - Vamsi K. Ithapu; Sathya N. Ravi; Vikas Singh (CoRR, 2015)

On the interplay of network structure and gradient convergence in deep learning. - Vamsi K. Ithapu; Sathya N. Ravi; Vikas Singh (Allerton, 2016)

Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks. - Seong Jae Hwang; Nagesh Adluru; Maxwell D. Collins; Sathya N. Ravi; Barbara B. Bendlin; Sterling C. Johnson; Vikas Singh (CVPR, 2016)

Experimental Design on a Budget for Sparse Linear Models and Applications. - Sathya N. Ravi; Vamsi K. Ithapu; Sterling C. Johnson; Vikas Singh (ICML, 2016)

Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Alzheimer's Disease. - Hao Henry Zhou; Vamsi K. Ithapu; Sathya Narayanan Ravi; Vikas Singh; Grace Wahba; Sterling C. Johnson (NIPS, 2016)

Filter Flow Made Practical: Massively Parallel and Lock-Free. - Sathya N. Ravi; Yunyang Xiong; Lopamudra Mukherjee; Vikas Singh (CVPR, 2017)

On architectural choices in deep learning: From network structure to gradient convergence and parameter estimation. - Vamsi K. Ithapu; Sathya N. Ravi; Vikas Singh (CoRR, 2017)

Tensorize, Factorize and Regularize: Robust Visual Relationship Learning. - Seong Jae Hwang; Sathya N. Ravi; Zirui Tao; Hyunwoo J. Kim; Maxwell D. Collins; Vikas Singh (CVPR, 2018)

A Biresolution Spectral Framework for Product Quantization. - Lopamudra Mukherjee; Sathya N. Ravi; Jiming Peng; Vikas Singh (CVPR, 2018)

Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision. - Sathya N. Ravi; Tuan Dinh; Vishnu Sai Rao Lokhande; Vikas Singh (CoRR, 2018)

Robust Blind Deconvolution via Mirror Descent. - Sathya N. Ravi; Ronak Mehta; Vikas Singh (CoRR, 2018)

Numerical Optimization to AI, and Back. - Sathya N. Ravi (AAAI, 2019)

Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence. - Sathya N. Ravi; Tuan Dinh; Vishnu Suresh Lokhande; Vikas Singh (AAAI, 2019)

Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks. - Yiyou Sun; Sathya N. Ravi; Vikas Singh (ICCV, 2019)

Generating Accurate Pseudo-labels via Hermite Polynomials for SSL Confidently. - Vishnu Suresh Lokhande; Sathya N. Ravi; Songwong Tasneeyapant; Abhay Venkatesh; Vikas Singh (CoRR, 2019)

A Deterministic Nonsmooth Frank Wolfe Algorithm with Coreset Guarantees. - Sathya N. Ravi; Maxwell D. Collins; Vikas Singh (INFORMS J. Optim., 2019)

Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains. - Sathya N. Ravi; Abhay Venkatesh; Glenn Moo Fung; Vikas Singh (AAAI, 2020)

Generating Accurate Pseudo-Labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations. - Vishnu Suresh Lokhande; Songwong Tasneeyapant; Abhay Venkatesh; Sathya N. Ravi; Vikas Singh (CVPR, 2020)

FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. - Vishnu Suresh Lokhande; Aditya Kumar Akash; Sathya N. Ravi; Vikas Singh (ECCV (12), 2020)

Learning Invariant Representations using Inverse Contrastive Loss. - Aditya Kumar Akash; Vishnu Suresh Lokhande; Sathya N. Ravi; Vikas Singh (AAAI, 2021)

Physarum Powered Differentiable Linear Programming Layers and Applications. - Zihang Meng; Sathya N. Ravi; Vikas Singh (AAAI, 2021)

Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators. - Zihang Meng; Vikas Singh; Sathya N. Ravi (ICCV, 2021)

You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling. - Zhanpeng Zeng; Yunyang Xiong; Sathya N. Ravi; Shailesh Acharya; Glenn Moo Fung; Vikas Singh (ICML, 2021)

Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs. - Zihang Meng; Lopamudra Mukherjee; Yichao Wu; Vikas Singh; Sathya N. Ravi (NeurIPS, 2021)

A variational approximation for analyzing the dynamics of panel data. - Jurijs Nazarovs; Rudrasis Chakraborty; Songwong Tasneeyapant; Sathya N. Ravi; Vikas Singh (UAI, 2021)

Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets. - Vishnu Suresh Lokhande; Rudrasis Chakraborty; Sathya N. Ravi; Vikas Singh (CVPR, 2022)

Deep Unlearning via Randomized Conditionally Independent Hessians. - Ronak Mehta; Sourav Pal; Vikas Singh; Sathya N. Ravi (CVPR, 2022)

Mixed Effects Neural ODE: A Variational Approximation for Analyzing the Dynamics of Panel Data. - Jurijs Nazarovs; Rudrasis Chakraborty; Songwong Tasneeyapant; Sathya N. Ravi; Vikas Singh (CoRR, 2022)

Performing Group Difference Testing on Graph Structured Data From GANs: Analysis and Applications in Neuroimaging. - Tuan Q. Dinh; Yunyang Xiong; Zhichun Huang; Tien Vo; Akshay Mishra; Won Hwa Kim; Sathya N. Ravi; Vikas Singh (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Robustness and Convergence of Mirror Descent for Blind Deconvolution. - Ronak Mehta; Sathya N. Ravi; Vikas Singh (ICASSP, 2023)

Controlled Differential Equations on Long Sequences via Non-standard Wavelets. - Sourav Pal; Zhanpeng Zeng; Sathya N. Ravi; Vikas Singh (ICML, 2023)

Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis. - Zhu Wang; Sourav Medya; Sathya N. Ravi (NeurIPS, 2023)

Using Intermediate Forward Iterates for Intermediate Generator Optimization. - Harsh Mishra; Jurijs Nazarovs; Manmohan Dogra; Sathya N. Ravi (CoRR, 2023)

Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis. - Zhu Wang; Sourav Medya; Sathya N. Ravi (CoRR, 2023)

Accelerated Neural Network Training with Rooted Logistic Objectives. - Zhu Wang; Praveen Raj Veluswami; Harsh Mishra; Sathya N. Ravi (CoRR, 2023)

Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization. - Hamidreza Almasi; Harsh Mishra; Balajee Vamanan; Sathya N. Ravi (ICLR, 2024)

IMPACT: A Large-scale Integrated Multimodal Patent Analysis and Creation Dataset for Design Patents. - Homaira Huda Shomee; Zhu Wang; Sathya N. Ravi; Sourav Medya (NeurIPS, 2024)

EmpatheticFIG at WASSA 2024 Empathy and Personality Shared Task: Predicting Empathy and Emotion in Conversations with Figurative Language. - Gyeongeun Lee; Zhu Wang; Sathya N. Ravi; Natalie Parde (WASSA, 2024)

A Comprehensive Survey on AI-based Methods for Patents. - Homaira Huda Shomee; Zhu Wang; Sathya N. Ravi; Sourav Medya (CoRR, 2024)

From Heart to Words: Generating Empathetic Responses via Integrated Figurative Language and Semantic Context Signals. - Gyeongeun Lee; Zhu Wang; Sathya N. Ravi; Natalie Parde (ACL (Findings), 2025)

A Survey on Patent Analysis: From NLP to Multimodal AI. - Homaira Huda Shomee; Zhu Wang; Sathya N. Ravi; Sourav Medya (ACL (1), 2025)

Optimizing Neural Network Training and Quantization with Rooted Logistic Objectives. - Zhu Wang; Praveen Raj Veluswami; Harsh Mishra; Sathya N. Ravi (AISTATS, 2025)

Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Images. - George R. Nahass; Zhu Wang; Homa Rashidisabet; Won Hwa Kim; Sasha Hubschman; Jeffrey C. Peterson; Ghasem Yazdanpanah; Chad A. Purnell; Pete Setabutr; Ann Q. Tran; Darvin Yi; Sathya N. Ravi (CoRR, 2025)