Sathya N. Ravi

59 papers A* 24A 2Misc 1Journal 26Unranked 6
YearRankTypeTitle / Venue / Authors
2025 — conf
A Survey on Patent Analysis: From NLP to Multimodal AI.
ACL (1)
Homaira Huda Shomee, Zhu Wang, Sathya N. Ravi, Sourav Medya
2025 — conf
DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding.
EMNLP (Findings)
Zhu Wang, Homaira Huda Shomee, Sathya N. Ravi, Sourav Medya
2025 J jnl
DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding.
CoRR
Zhu Wang, Homaira Huda Shomee, Sathya N. Ravi, Sourav Medya
2025 — conf
From Heart to Words: Generating Empathetic Responses via Integrated Figurative Language and Semantic Context Signals.
ACL (Findings)
Gyeongeun Lee, Zhu Wang, Sathya N. Ravi, Natalie Parde
2025 A conf
Optimizing Neural Network Training and Quantization with Rooted Logistic Objectives.
AISTATS
Zhu Wang, Praveen Raj Veluswami, Harsh Mishra, Sathya N. Ravi
2025 J jnl
Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Images.
CoRR
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
2025 J jnl
Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Images.
Trans. Mach. Learn. Res.
George R. Nahass, Zhu Wang, Homa Rashidisabet, Won Hwa Kim, Sasha Hubschman, Jeffrey C. Peterson, Pete Setabutr, Chad A. Purnell, Ann Q. Tran, Darvin Yi, Sathya N. Ravi
2024 J jnl
A Comprehensive Survey on AI-based Methods for Patents.
CoRR
Homaira Huda Shomee, Zhu Wang, Sathya N. Ravi, Sourav Medya
2024 — conf
EmpatheticFIG at WASSA 2024 Empathy and Personality Shared Task: Predicting Empathy and Emotion in Conversations with Figurative Language.
WASSA
Gyeongeun Lee, Zhu Wang, Sathya N. Ravi, Natalie Parde
2024 A* conf
Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization.
ICLR
Hamidreza Almasi, Harsh Mishra, Balajee Vamanan, Sathya N. Ravi
2024 A* conf
IMPACT: A Large-scale Integrated Multimodal Patent Analysis and Creation Dataset for Design Patents.
NeurIPS
Homaira Huda Shomee, Zhu Wang, Sathya N. Ravi, Sourav Medya
2023 J jnl
Accelerated Neural Network Training with Rooted Logistic Objectives.
CoRR
Zhu Wang, Praveen Raj Veluswami, Harsh Mishra, Sathya N. Ravi
2023 A* conf
Controlled Differential Equations on Long Sequences via Non-standard Wavelets.
ICML
Sourav Pal, Zhanpeng Zeng, Sathya N. Ravi, Vikas Singh
2023 J jnl
Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis.
CoRR
Zhu Wang, Sourav Medya, Sathya N. Ravi
2023 J jnl
Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization.
CoRR
Hamidreza Almasi, Harsh Mishra, Balajee Vamanan, Sathya N. Ravi
2023 A* conf
Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis.
NeurIPS
Zhu Wang, Sourav Medya, Sathya N. Ravi
2023 Misc conf
Robustness and Convergence of Mirror Descent for Blind Deconvolution.
ICASSP
Ronak Mehta, Sathya N. Ravi, Vikas Singh
2023 J jnl
Using Intermediate Forward Iterates for Intermediate Generator Optimization.
CoRR
Harsh Mishra, Jurijs Nazarovs, Manmohan Dogra, Sathya N. Ravi
2022 A* conf
Deep Unlearning via Randomized Conditionally Independent Hessians.
CVPR
Ronak Mehta, Sourav Pal, Vikas Singh, Sathya N. Ravi
2022 J jnl
Deep Unlearning via Randomized Conditionally Independent Hessians.
CoRR
Ronak Mehta, Sourav Pal, Vikas Singh, Sathya N. Ravi
2022 A* conf
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets.
CVPR
Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh
2022 J jnl
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets.
CoRR
Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh
2022 J jnl
Mixed Effects Neural ODE: A Variational Approximation for Analyzing the Dynamics of Panel Data.
CoRR
Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant, Sathya N. Ravi, Vikas Singh
2022 J jnl
Performing Group Difference Testing on Graph Structured Data From GANs: Analysis and Applications in Neuroimaging.
IEEE Trans. Pattern Anal. Mach. Intell.
Tuan Q. Dinh, Yunyang Xiong, Zhichun Huang, Tien Vo, Akshay Mishra, Won Hwa Kim, Sathya N. Ravi, Vikas Singh
2021 A conf
A variational approximation for analyzing the dynamics of panel data.
UAI
Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant, Sathya N. Ravi, Vikas Singh
2021 A* conf
Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs.
NeurIPS
Zihang Meng, Lopamudra Mukherjee, Yichao Wu, Vikas Singh, Sathya N. Ravi
2021 A* conf
Learning Invariant Representations using Inverse Contrastive Loss.
AAAI
Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh
2021 J jnl
Learning Invariant Representations using Inverse Contrastive Loss.
CoRR
Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh
2021 A* conf
Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators.
ICCV
Zihang Meng, Vikas Singh, Sathya N. Ravi
2021 J jnl
Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators.
CoRR
Zihang Meng, Vikas Singh, Sathya N. Ravi
2021 A* conf
Physarum Powered Differentiable Linear Programming Layers and Applications.
AAAI
Zihang Meng, Sathya N. Ravi, Vikas Singh
2021 A* conf
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling.
ICML
Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Moo Fung, Vikas Singh
2021 J jnl
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling.
CoRR
Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Fung, Vikas Singh
2020 — conf
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret.
ECCV (12)
Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh
2020 J jnl
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret.
CoRR
Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh
2020 A* conf
Generating Accurate Pseudo-Labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations.
CVPR
Vishnu Suresh Lokhande, Songwong Tasneeyapant, Abhay Venkatesh, Sathya N. Ravi, Vikas Singh
2020 A* conf
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains.
AAAI
Sathya N. Ravi, Abhay Venkatesh, Glenn Moo Fung, Vikas Singh
2020 J jnl
Physarum Powered Differentiable Linear Programming Layers and Applications.
CoRR
Zihang Meng, Sathya N. Ravi, Vikas Singh
2019 J jnl
A Deterministic Nonsmooth Frank Wolfe Algorithm with Coreset Guarantees.
INFORMS J. Optim.
Sathya N. Ravi, Maxwell D. Collins, Vikas Singh
2019 A* conf
Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks.
ICCV
Yiyou Sun, Sathya N. Ravi, Vikas Singh
2019 A* conf
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence.
AAAI
Sathya N. Ravi, Tuan Dinh, Vishnu Suresh Lokhande, Vikas Singh
2019 J jnl
Generating Accurate Pseudo-labels via Hermite Polynomials for SSL Confidently.
CoRR
Vishnu Suresh Lokhande, Sathya N. Ravi, Songwong Tasneeyapant, Abhay Venkatesh, Vikas Singh
2019 A* conf
Numerical Optimization to AI, and Back.
AAAI
Sathya N. Ravi
2019 J jnl
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization offers Significant Performance and Efficiency Gains.
CoRR
Sathya N. Ravi, Abhay Venkatesh, Glenn Moo Fung, Vikas Singh
2018 A* conf
A Biresolution Spectral Framework for Product Quantization.
CVPR
Lopamudra Mukherjee, Sathya N. Ravi, Jiming Peng, Vikas Singh
2018 J jnl
Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision.
CoRR
Sathya N. Ravi, Tuan Dinh, Vishnu Sai Rao Lokhande, Vikas Singh
2018 J jnl
Robust Blind Deconvolution via Mirror Descent.
CoRR
Sathya N. Ravi, Ronak Mehta, Vikas Singh
2018 A* conf
Tensorize, Factorize and Regularize: Robust Visual Relationship Learning.
CVPR
Seong Jae Hwang, Sathya N. Ravi, Zirui Tao, Hyunwoo J. Kim, Maxwell D. Collins, Vikas Singh
2017 J jnl
A Deterministic Nonsmooth Frank Wolfe Algorithm with Coreset Guarantees.
CoRR
Sathya N. Ravi, Maxwell D. Collins, Vikas Singh
2017 A* conf
Filter Flow Made Practical: Massively Parallel and Lock-Free.
CVPR
Sathya N. Ravi, Yunyang Xiong, Lopamudra Mukherjee, Vikas Singh
2017 J jnl
On architectural choices in deep learning: From network structure to gradient convergence and parameter estimation.
CoRR
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
2016 A* conf
Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks.
CVPR
Seong Jae Hwang, Nagesh Adluru, Maxwell D. Collins, Sathya N. Ravi, Barbara B. Bendlin, Sterling C. Johnson, Vikas Singh
2016 A* conf
Experimental Design on a Budget for Sparse Linear Models and Applications.
ICML
Sathya N. Ravi, Vamsi K. Ithapu, Sterling C. Johnson, Vikas Singh
2016 — conf
On the interplay of network structure and gradient convergence in deep learning.
Allerton
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
2015 A* conf
A Projection Free Method for Generalized Eigenvalue Problem with a Nonsmooth Regularizer.
ICCV
Seong Jae Hwang, Maxwell D. Collins, Sathya N. Ravi, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson, Vikas Singh
2015 A* conf
An NMF Perspective on Binary Hashing.
ICCV
Lopamudra Mukherjee, Sathya N. Ravi, Vamsi K. Ithapu, Tyler Holmes, Vikas Singh
2015 J jnl
Convergence of gradient based pre-training in Denoising autoencoders.
CoRR
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
2015 A* conf
On Statistical Analysis of Neuroimages with Imperfect Registration.
ICCV
Won Hwa Kim, Sathya N. Ravi, Sterling C. Johnson, Ozioma C. Okonkwo, Vikas Singh
2015 J jnl
On the interplay of network structure and gradient convergence in deep learning.
CoRR
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh