Ajay Jaiswal

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 56

Top Topics

Face Recognition

Nonparametric Discriminant Analysis

Atmospheric Turbulence

Top Venues

J. Informetrics

Publications

Tianhao Li, Sandesh Shetty, Advaith Kamath, Ajay Jaiswal, Xiaoqian Jiang, Ying Ding, Yejin Kim
CancerGPT for few shot drug pair synergy prediction using large pretrained language models. npj Digit. Medicine 7 (1) (2024)
Ajay Jaiswal, Bodun Hu, Lu Yin, Yeonju Ro, Shiwei Liu, Tianlong Chen, Aditya Akella
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. CoRR (2024)
Feng Liu, Ryan Ashbaugh, Nicholas Chimitt, Najmul Hassan, Ali Hassani, Ajay Jaiswal, Minchul Kim, Zhiyuan Mao, Christopher Perry, Zhiyuan Ren, Yiyang Su, Pegah Varghaei, Kai Wang, Stanley H. Chan, Arun Ross, Humphrey Shi, Zhangyang Wang, Anil Jain, Xiaoming Liu
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude. WACV (2024)
Ritu Bibyan, Sameer Anand, Ajay Jaiswal, Anu G. Aggarwal
Bug severity prediction using LDA and sentiment scores: A CNN approach. Expert Syst. J. Knowl. Eng. 41 (7) (2024)
Zhenyu Zhang, Ajay Jaiswal, Lu Yin, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang
Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients. CoRR (2024)
Ajay Jaiswal, Nurendra Choudhary, Ravinarayana Adkathimar, Muthu P. Alagappan, Gaurush Hiranandani, Ying Ding, Zhangyang Wang, Edward W. Huang, Karthik Subbian
All Against Some: Efficient Integration of Large Language Models for Message Passing in Graph Neural Networks. CoRR (2024)
Runjin Chen, Tong Zhao, Ajay Jaiswal, Neil Shah, Zhangyang Wang
LLaGA: Large Language and Graph Assistant. CoRR (2024)
Gregory Holste, Yiliang Zhou, Song Wang, Ajay Jaiswal, Mingquan Lin, Sherry Zhuge, Yuzhe Yang, Dongkyun Kim, Trong-Hieu Nguyen Mau, Minh-Triet Tran, Jaehyup Jeong, Wongi Park, Jongbin Ryu, Feng Hong, Arsh Verma, Yosuke Yamagishi, Changhyun Kim, Hyeryeong Seo, Myungjoo Kang, Leo Anthony Celi, Zhiyong Lu, Ronald M. Summers, George Shih, Zhangyang Wang, Yifan Peng
Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge. Medical Image Anal. 97 (2024)
Ajay Jaiswal, Lu Yin, Zhenyu Zhang, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang
From GaLore to WeLore: How Low-Rank Weights Non-uniformly Emerge from Low-Rank Gradients. CoRR (2024)
Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer, Brian R. Bartoldson, Ajay Jaiswal, Kaidi Xu, Bhavya Kailkhura, Dan Hendrycks, Dawn Song, Zhangyang Wang, Bo Li
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression. CoRR (2024)
Tianhao Li, Sandesh Shetty, Advaith Kamath, Ajay Jaiswal, Xianqian Jiang, Ying Ding, Yejin Kim
CancerGPT: Few-shot Drug Pair Synergy Prediction using Large Pre-trained Language Models. CoRR (2023)
Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau, Yifan Peng, Ying Ding, Zhangyang Wang
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances. WACV (2023)
Huimin Xu, Redoan Rahman, Ajay Jaiswal, Julia Fensel, Abhinav Peri, Kamesh Peri, Griffin M. Weber, Ying Ding
Disparity in the Evolving COVID-19 Collaboration Network. iConference (1) (2023)
Feng Liu, Ryan Ashbaugh, Nicholas Chimitt, Najmul Hassan, Ali Hassani, Ajay Jaiswal, Minchul Kim, Zhiyuan Mao, Christopher Perry, Zhiyuan Ren, Yiyang Su, Pegah Varghaei, Kai Wang, Xingguang Zhang, Stanley H. Chan, Arun Ross, Humphrey Shi, Zhangyang Wang, Anil K. Jain, Xiaoming Liu
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude. CoRR (2023)
Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. CoRR (2023)
Ajay Jaiswal, Xingguang Zhang, Stanley H. Chan, Zhangyang Wang
Physics-Driven Turbulence Image Restoration with Stochastic Refinement. CoRR (2023)
Gregory Holste, Ziyu Jiang, Ajay Jaiswal, Maria Hanna, Shlomo Minkowitz, Alan C. Legasto, Joanna G. Escalon, Sharon Steinberger, Mark Bittman, Thomas C. Shen, Ying Ding, Ronald M. Summers, George Shih, Yifan Peng, Zhangyang Wang
How Does Pruning Impact Long-Tailed Multi-label Medical Image Classifiers? MICCAI (5) (2023)
Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. CoRR (2023)
Ajay Jaiswal, Xingguang Zhang, Stanley H. Chan, Zhangyang Wang
Physics-Driven Turbulence Image Restoration with Stochastic Refinement. ICCV (2023)
Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. CoRR (2023)
Ajay Jaiswal, Zhe Gan, Xianzhi Du, Bowen Zhang, Zhangyang Wang, Yinfei Yang
Compressing LLMs: The Truth is Rarely Pure and Never Simple. CoRR (2023)
Lu Yin, Shiwei Liu, Ajay Jaiswal, Souvik Kundu, Zhangyang Wang
Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity. CoRR (2023)
Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Jaiswal, Zhangyang Wang
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! CoRR (2023)
Gregory Holste, Yiliang Zhou, Song Wang, Ajay Jaiswal, Mingquan Lin, Sherry Zhuge, Yuzhe Yang, Dongkyun Kim, Trong-Hieu Nguyen Mau, Minh-Triet Tran, Jaehyup Jeong, Wongi Park, Jongbin Ryu, Feng Hong, Arsh Verma, Yosuke Yamagishi, Changhyun Kim, Hyeryeong Seo, Myungjoo Kang, Leo Anthony Celi, Zhiyong Lu, Ronald M. Summers, George Shih, Zhangyang Wang, Yifan Peng
Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge. CoRR (2023)
Ritu Bibyan, Sameer Anand, Ajay Jaiswal, Anu G. Aggarwal
Software reliability testing coverage model using feed-forward back propagation neural network. Int. J. Model. Identif. Control. 43 (2) (2023)
Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. NeurIPS (2023)
Gregory Holste, Ziyu Jiang, Ajay Jaiswal, Maria Hanna, Shlomo Minkowitz, Alan C. Legasto, Joanna G. Escalon, Sharon Steinberger, Mark Bittman, Thomas C. Shen, Ying Ding, Ronald M. Summers, George Shih, Yifan Peng, Zhangyang Wang
How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers? CoRR (2023)
Tianlong Chen, Zhenyu Zhang, Ajay Jaiswal, Shiwei Liu, Zhangyang Wang
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. CoRR (2023)
Huimin Xu, Redoan Rahman, Ajay Jaiswal, Julia Fensel, Abhinav Peri, Ka-mesh Peri, Griffin M. Weber, Ying Ding
Disparity in the Evolving COVID-19 Collaboration Network. CoRR (2023)
Zhiyuan Mao, Ajay Jaiswal, Zhangyang Wang, Stanley H. Chan
Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and a New Physics-Inspired Transformer Model. ECCV (19) (2022)
Ambarish G. Mohapatra, Jaideep Talukdar, Tarini Ch. Mishra, Sameer Anand, Ajay Jaiswal, Ashish Khanna, Deepak Gupta
Fiber Bragg grating sensors driven structural health monitoring by using multimedia-enabled iot and big data technology. Multim. Tools Appl. 81 (24) (2022)
Meijun Liu, Ajay Jaiswal, Yi Bu, Chao Min, Sijie Yang, Zhibo Liu, Daniel Daniel Acuña, Ying Ding
Team formation and team impact: The balance between team freshness and repeat collaboration. J. Informetrics 16 (4) (2022)
Meijun Liu, Ning Zhang, Xiao Hu, Ajay Jaiswal, Jian Xu, Hong Chen, Ying Ding, Yi Bu
Further divided gender gaps in research productivity and collaboration during the COVID-19 pandemic: Evidence from coronavirus-related literature. J. Informetrics 16 (2) (2022)
Ajay Jaiswal, Peihao Wang, Tianlong Chen, Justin F. Rousseau, Ying Ding, Zhangyang Wang
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again. CoRR (2022)
Ajay Jaiswal, Haoyu Ma, Tianlong Chen, Ying Ding, Zhangyang Wang
Training Your Sparse Neural Network Better with Any Mask. CoRR (2022)
Meijun Liu, Ajay Jaiswal, Yi Bu, Chao Min, Sijie Yang, Zhibo Liu, Daniel Daniel Acuña, Ying Ding
Team formation and team performance: The balance between team freshness and repeat collaboration. CoRR (2022)
Ajay Jaiswal, Peihao Wang, Tianlong Chen, Justin F. Rousseau, Ying Ding, Zhangyang Wang
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again. NeurIPS (2022)
Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau, Yifan Peng, Ying Ding, Zhangyang Wang
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances. CoRR (2022)
Zhiyuan Mao, Ajay Jaiswal, Zhangyang Wang, Stanley H. Chan
Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model. CoRR (2022)
Ajay Jaiswal, Kumar Ashutosh, Justin F. Rousseau, Yifan Peng, Zhangyang Wang, Ying Ding
RoS-KD: A Robust Stochastic Knowledge Distillation Approach for Noisy Medical Imaging. ICDM (2022)
Ajay Jaiswal, Kumar Ashutosh, Justin F. Rousseau, Yifan Peng, Zhangyang Wang, Ying Ding
RoS-KD: A Robust Stochastic Knowledge Distillation Approach for Noisy Medical Imaging. CoRR (2022)
Ajay Jaiswal, Tianhao Li, Cyprian Zander, Yan Han, Justin F. Rousseau, Yifan Peng, Ying Ding
SCALP - Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata. ICDM (2021)
Ajay Jaiswal, Tianhao Li, Cyprian Zander, Yan Han, Justin F. Rousseau, Yifan Peng, Ying Ding
SCALP - Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata. CoRR (2021)
Ajay Jaiswal, Meijun Liu, Ying Ding
Understanding Parachuting Collaboration. iConference (1) (2021)
Yan Han, Chongyan Chen, Liyan Tang, Mingquan Lin, Ajay Jaiswal, Song Wang, Ahmed H. Tewfik, George Shih, Ying Ding, Yifan Peng
Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays. AMIA (2021)
Ajay Jaiswal, Liyan Tang, Meheli Ghosh, Justin Rousseau, Yifan Peng, Ying Ding
RadBERT-CL: Factually-Aware Contrastive Learning For Radiology Report Classification. CoRR (2021)
Ajay Jaiswal, Liyan Tang, Meheli Ghosh, Justin F. Rousseau, Yifan Peng, Ying Ding
RadBERT-CL: Factually-Aware Contrastive Learning For Radiology Report Classification. ML4H@NeurIPS (2021)
Vertika Srivastava, Sudeep Kumar Sahoo, Yeon Hyang Kim, Rohit R. R, Mayank Raj, Ajay Jaiswal
Team Solomon at SemEval-2020 Task 4: Be Reasonable: Exploiting Large-scale Language Models for Commonsense Reasoning. SemEval@COLING (2020)
Yan Han, Chongyan Chen, Liyan Tang, Mingquan Lin, Ajay Jaiswal, Ying Ding, Yifan Peng
Using Radiomics as Prior Knowledge for Abnormality Classification and Localization in Chest X-rays. CoRR (2020)
Aakash Aakash, Ajay Jaiswal
Segmentation and Ranking of Online Reviewer Community: The Role of Reviewers' Frequency, Helpfulness, and Recency. Int. J. E Adopt. 12 (1) (2020)
Mayank Raj, Ajay Jaiswal, Rohit R. R, Ankita Gupta, Sudeep Kumar Sahoo, Vertika Srivastava, Yeon Hyang Kim
Solomon at SemEval-2020 Task 11: Ensemble Architecture for Fine-Tuned Propaganda Detection in News Articles. CoRR (2020)
Mayank Raj, Ajay Jaiswal, Rohit R. R, Ankita Gupta, Sudeep Kumar Sahoo, Vertika Srivastava, Yeon Hyang Kim
Solomon at SemEval-2020 Task 11: Ensemble Architecture for Fine-Tuned Propaganda Detection in News Articles. SemEval@COLING (2020)
Mayank Singh, Ajay Jaiswal, Priya Shree, Arindam Pal, Animesh Mukherjee, Pawan Goyal
Understanding the Impact of Early Citers on Long-Term Scientific Impact. JCDL (2017)
Mayank Singh, Ajay Jaiswal, Priya Shree, Arindam Pal, Animesh Mukherjee, Pawan Goyal
Understanding the Impact of Early Citers on Long-Term Scientific Impact. CoRR (2017)
Nitin Kumar, Maheep Singh, Mahesh Chandra Govil, Emmanuel S. Pilli, Ajay Jaiswal
Salient Object Detection in Noisy Images. Canadian Conference on AI (2016)
Nitin Kumar, Ramesh K. Agrawal, Ajay Jaiswal
Incremental and Decremental Nonparametric Discriminant Analysis for Face Recognition. Comput. Informatics 35 (5) (2016)
Ajay Jaiswal, Nitin Kumar, R. K. Agrawal
Analysis and evaluation of regression-based methods for facial pose classification. Int. J. Appl. Pattern Recognit. 2 (1) (2015)
Nitin Kumar, R. K. Agrawal, Ajay Jaiswal
A Comparative Study of Linear Discriminant and Linear Regression Based Methods for Expression Invariant Face Recognition. SIRS (2014)
Nitin Kumar, R. K. Agrawal, Ajay Jaiswal
Incremental and Decremental Exponential Discriminant Analysis for Face Recognition. Int. J. Comput. Vis. Image Process. 4 (1) (2014)
Ajay Jaiswal, Nitin Kumar, R. K. Agrawal
Local Linear Regression on Hybrid Eigenfaces for Pose Invariant Face Recognition. Int. J. Comput. Vis. Image Process. 2 (2) (2012)
Ajay Jaiswal, Nitin Kumar, Ramesh K. Agrawal
A Hybrid of Principal Component Analysis and Partial Least Squares for Face Recognition across Pose. CIARP (2012)
Ajay Jaiswal, Nitin Kumar, R. K. Agrawal
Statistical Framework for Facial Pose Classification. MICAI (1) (2012)
Ajay Jaiswal, Meena Sharma
Expert Webest Tool: A Web Based Application, Estimate the Cost and Risk of Software Project Using Function Points. ACITY (2) (2012)
Nitin Kumar, Ajay Jaiswal, Ramesh K. Agrawal
Performance evaluation of subspace methods to tackle small sample size problem in face recognition. ICACCI (2012)
Ajay Jaiswal, Ramesh K. Agrawal, Nitin Kumar
Performance evaluation of linear subspace methods for face recognition under illumination variation. C3S2E (2011)