Performance evaluation of linear subspace methods for face recognition under illumination variation. - Ajay Jaiswal; Ramesh K. Agrawal; Nitin Kumar 001 (C3S2E, 2011)

Expert Webest Tool: A Web Based Application, Estimate the Cost and Risk of Software Project Using Function Points. - Ajay Jaiswal; Meena Sharma (ACITY (2), 2012)

A Hybrid of Principal Component Analysis and Partial Least Squares for Face Recognition across Pose. - Ajay Jaiswal; Nitin Kumar 001; Ramesh K. Agrawal (CIARP, 2012)

Performance evaluation of subspace methods to tackle small sample size problem in face recognition. - Nitin Kumar 001; Ajay Jaiswal; Ramesh K. Agrawal (ICACCI, 2012)

Statistical Framework for Facial Pose Classification. - Ajay Jaiswal; Nitin Kumar 001; R. K. Agrawal 001 (MICAI (1), 2012)

Local Linear Regression on Hybrid Eigenfaces for Pose Invariant Face Recognition. - Ajay Jaiswal; Nitin Kumar 001; R. K. Agrawal 001 (Int. J. Comput. Vis. Image Process., 2012)

A Comparative Study of Linear Discriminant and Linear Regression Based Methods for Expression Invariant Face Recognition. - Nitin Kumar 001; R. K. Agrawal 001; Ajay Jaiswal (SIRS, 2014)

Incremental and Decremental Exponential Discriminant Analysis for Face Recognition. - Nitin Kumar 001; R. K. Agrawal 001; Ajay Jaiswal (Int. J. Comput. Vis. Image Process., 2014)

Analysis and evaluation of regression-based methods for facial pose classification. - Ajay Jaiswal; Nitin Kumar 001; R. K. Agrawal 001 (Int. J. Appl. Pattern Recognit., 2015)

Salient Object Detection in Noisy Images. - Nitin Kumar 001; Maheep Singh; Mahesh Chandra Govil; Emmanuel S. Pilli; Ajay Jaiswal (Canadian AI, 2016)

Incremental and Decremental Nonparametric Discriminant Analysis for Face Recognition. - Nitin Kumar 001; Ramesh K. Agrawal; Ajay Jaiswal (Comput. Informatics, 2016)

Understanding the Impact of Early Citers on Long-Term Scientific Impact. - Mayank Singh 001; Ajay Jaiswal; Priya Shree; Arindam Pal 001; Animesh Mukherjee 001; Pawan Goyal 002 (JCDL, 2017)

Solomon at SemEval-2020 Task 11: Ensemble Architecture for Fine-Tuned Propaganda Detection in News Articles. - Mayank Raj; Ajay Jaiswal; Rohit R. R; Ankita Gupta; Sudeep Kumar Sahoo; Vertika Srivastava; Yeon Hyang Kim (SemEval@COLING, 2020)

Team Solomon at SemEval-2020 Task 4: Be Reasonable: Exploiting Large-scale Language Models for Commonsense Reasoning. - Vertika Srivastava; Sudeep Kumar Sahoo; Yeon Hyang Kim; Rohit R. R; Mayank Raj; Ajay Jaiswal (SemEval@COLING, 2020)

Using Radiomics as Prior Knowledge for Abnormality Classification and Localization in Chest X-rays. - Yan Han 001; Chongyan Chen; Liyan Tang; Mingquan Lin; Ajay Jaiswal; Ying Ding 001; Yifan Peng 002 (CoRR, 2020)

Segmentation and Ranking of Online Reviewer Community: The Role of Reviewers' Frequency, Helpfulness, and Recency. - Aakash Aakash; Ajay Jaiswal (Int. J. E Adopt., 2020)

Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays. - Yan Han 001; Chongyan Chen; Liyan Tang; Mingquan Lin; Ajay Jaiswal; Song Wang 026; Ahmed H. Tewfik; George Shih; Ying Ding 001; Yifan Peng 002 (AMIA, 2021)

SCALP - Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata. - Ajay Jaiswal; Tianhao Li; Cyprian Zander; Yan Han 001; Justin F. Rousseau; Yifan Peng 002; Ying Ding 001 (ICDM, 2021)

Understanding Parachuting Collaboration. - Ajay Jaiswal; Meijun Liu; Ying Ding 001 (iConference (1), 2021)

RadBERT-CL: Factually-Aware Contrastive Learning For Radiology Report Classification. - Ajay Jaiswal; Liyan Tang; Meheli Ghosh; Justin F. Rousseau; Yifan Peng 002; Ying Ding 001 (ML4H@NeurIPS, 2021)

Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and a New Physics-Inspired Transformer Model. - Zhiyuan Mao; Ajay Jaiswal; Zhangyang Wang; Stanley H. Chan (ECCV (19), 2022)

RoS-KD: A Robust Stochastic Knowledge Distillation Approach for Noisy Medical Imaging. - Ajay Jaiswal; Kumar Ashutosh; Justin F. Rousseau; Yifan Peng 002; Zhangyang Wang; Ying Ding 001 (ICDM, 2022)

Training Your Sparse Neural Network Better with Any Mask. - Ajay Kumar Jaiswal; Haoyu Ma; Tianlong Chen 001; Ying Ding 001; Zhangyang Wang (ICML, 2022)

Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again. - Ajay Jaiswal; Peihao Wang; Tianlong Chen 001; Justin F. Rousseau; Ying Ding 001; Zhangyang Wang (NeurIPS, 2022)

Team formation and team performance: The balance between team freshness and repeat collaboration. - Meijun Liu; Ajay Jaiswal; Yi Bu 001; Chao Min; Sijie Yang; Zhibo Liu; Daniel Daniel Acuña; Ying Ding 001 (CoRR, 2022)

Team formation and team impact: The balance between team freshness and repeat collaboration. - Meijun Liu; Ajay Jaiswal; Yi Bu 001; Chao Min; Sijie Yang; Zhibo Liu; Daniel Daniel Acuña; Ying Ding 001 (J. Informetrics, 2022)

Further divided gender gaps in research productivity and collaboration during the COVID-19 pandemic: Evidence from coronavirus-related literature. - Meijun Liu; Ning Zhang 041; Xiao Hu; Ajay Jaiswal; Jian Xu 003; Hong Chen; Ying Ding 001; Yi Bu 001 (J. Informetrics, 2022)

Fiber Bragg grating sensors driven structural health monitoring by using multimedia-enabled iot and big data technology. - Ambarish G. Mohapatra; Jaideep Talukdar; Tarini Ch. Mishra; Sameer Anand; Ajay Jaiswal; Ashish Khanna; Deepak Gupta 002 (Multim. Tools Appl., 2022)

Physics-Driven Turbulence Image Restoration with Stochastic Refinement. - Ajay Jaiswal; Xingguang Zhang; Stanley H. Chan; Zhangyang Wang (ICCV, 2023)

Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. - Tianlong Chen 001; Zhenyu Zhang 015; Ajay Kumar Jaiswal; Shiwei Liu 003; Zhangyang Wang (ICLR, 2023)

Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! - Shiwei Liu 003; Tianlong Chen 001; Zhenyu Zhang 015; Xuxi Chen; Tianjin Huang; Ajay Kumar Jaiswal; Zhangyang Wang (ICLR, 2023)

Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. - Ajay Kumar Jaiswal; Shiwei Liu 003; Tianlong Chen 001; Ying Ding 001; Zhangyang Wang (ICML, 2023)

Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. - Ajay Kumar Jaiswal; Shiwei Liu 003; Tianlong Chen 001; Ying Ding 001; Zhangyang Wang (ICML, 2023)

Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation. - Wenqing Zheng; S. P. Sharan; Ajay Kumar Jaiswal; Kevin Wang; Yihan Xi; Dejia Xu; Zhangyang Wang (ICML, 2023)

Disparity in the Evolving COVID-19 Collaboration Network. - Huimin Xu; Redoan Rahman; Ajay Jaiswal; Julia Fensel; Abhinav Peri; Kamesh Peri; Griffin M. Weber; Ying Ding 001 (iConference (1), 2023)

How Does Pruning Impact Long-Tailed Multi-label Medical Image Classifiers? - 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 001; Ronald M. Summers; et al. (MICCAI (5), 2023)

The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. - Ajay Jaiswal; Shiwei Liu 003; Tianlong Chen 001; Zhangyang Wang (NeurIPS, 2023)

Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances. - Ajay Jaiswal; Tianlong Chen 001; Justin F. Rousseau; Yifan Peng 002; Ying Ding 001; Zhangyang Wang (WACV, 2023)

CancerGPT: Few-shot Drug Pair Synergy Prediction using Large Pre-trained Language Models. - Tianhao Li; Sandesh Shetty; Advaith Kamath; Ajay Jaiswal; Xianqian Jiang; Ying Ding 001; Yejin Kim 001 (CoRR, 2023)

FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude. - Feng Liu 037; Ryan Ashbaugh; Nicholas Chimitt; Najmul Hassan; Ali Hassani 001; Ajay Jaiswal; Minchul Kim; Zhiyuan Mao; Christopher Perry; Zhiyuan Ren; Yiyang Su; Pegah Varghaei; et al. (CoRR, 2023)

Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity. - Lu Yin 006; Shiwei Liu 003; Ajay Jaiswal; Souvik Kundu 009; Zhangyang Wang (CoRR, 2023)

Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge. - Gregory Holste; Yiliang Zhou; Song Wang 013; Ajay Jaiswal; Mingquan Lin; Sherry Zhuge; Yuzhe Yang 003; Dongkyun Kim; Trong-Hieu Nguyen Mau; Minh-Triet Tran; Jaehyup Jeong; Wongi Park; et al. (CoRR, 2023)

Software reliability testing coverage model using feed-forward back propagation neural network. - Ritu Bibyan; Sameer Anand; Ajay Jaiswal; Anu G. Aggarwal 001 (Int. J. Model. Identif. Control., 2023)

Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning. - Abhinav Bandari; Lu Yin 006; Cheng-Yu Hsieh; Ajay Jaiswal; Tianlong Chen 001; Li Shen 008; Ranjay Krishna; Shiwei Liu 003 (EMNLP, 2024)

FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. - Ajay Jaiswal; Bodun Hu; Lu Yin 006; Yeonju Ro; Tianlong Chen 001; Shiwei Liu 003; Aditya Akella (EMNLP, 2024)

Compressing LLMs: The Truth is Rarely Pure and Never Simple. - Ajay Kumar Jaiswal; Zhe Gan; Xianzhi Du; Bowen Zhang; Zhangyang Wang; Yinfei Yang (ICLR, 2024)

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs. - Lu Yin 006; Ajay Kumar Jaiswal; Shiwei Liu 003; Souvik Kundu 009; Zhangyang Wang (ICML, 2024)

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. - Lu Yin 006; You Wu 001; Zhenyu Zhang 015; Cheng-Yu Hsieh; Yaqing Wang 007; Yiling Jia; Gen Li 012; Ajay Kumar Jaiswal; Mykola Pechenizkiy; Yi Liang; Michael Bendersky; Zhangyang Wang; et al. (ICML, 2024)

LLaGA: Large Language and Graph Assistant. - Runjin Chen; Tong Zhao 003; Ajay Kumar Jaiswal; Neil Shah; Zhangyang Wang (ICML, 2024)

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression. - Junyuan Hong; Jinhao Duan; Chenhui Zhang; Zhangheng Li; Chulin Xie; Kelsey Lieberman; James Diffenderfer; Brian R. Bartoldson; Ajay Kumar Jaiswal; Kaidi Xu; Bhavya Kailkhura; Dan Hendrycks; et al. (ICML, 2024)

Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once. - Zhangheng Li; Shiwei Liu 003; Tianlong Chen 001; Ajay Kumar Jaiswal; Zhenyu Zhang 015; Dilin Wang; Raghuraman Krishnamoorthi; Shiyu Chang; Zhangyang Wang (ICML, 2024)

Path-RAG: Knowledge-Guided Key Region Retrieval for Open-ended Pathology Visual Question Answering. - Awais Naeem; Tianhao Li; Huang-Ru Liao; Jiawei Xu 006; Aby M. Mathew; Zehao Zhu; Zhen Tan 001; Ajay Kumar Jaiswal; Raffi A. Salibian; Ziniu Hu; Tianlong Chen 001; Ying Ding 001 (ML4H@NeurIPS, 2024)

FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude. - Feng Liu 037; Ryan Ashbaugh; Nicholas Chimitt; Najmul Hassan; Ali Hassani 001; Ajay Jaiswal; Minchul Kim; Zhiyuan Mao; Christopher Perry; Zhiyuan Ren; Yiyang Su; Pegah Varghaei; et al. (WACV, 2024)

From GaLore to WeLore: How Low-Rank Weights Non-uniformly Emerge from Low-Rank Gradients. - Ajay Jaiswal; Lu Yin 006; Zhenyu Zhang 015; Shiwei Liu 003; Jiawei Zhao; Yuandong Tian; Zhangyang Wang (CoRR, 2024)

All Against Some: Efficient Integration of Large Language Models for Message Passing in Graph Neural Networks. - Ajay Jaiswal; Nurendra Choudhary; Ravinarayana Adkathimar; Muthu P. Alagappan; Gaurush Hiranandani; Ying Ding 001; Zhangyang Wang; Edward W. Huang; Karthik Subbian (CoRR, 2024)

Modeling the impact of noise and uncertain operational environment on software release decisions considering testing coverage-based SRGM. - Sameer Anand; Ajay Jaiswal; Vibha Verma; Atul Singh (Intell. Decis. Technol., 2024)

Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge. - Gregory Holste; Yiliang Zhou; Song Wang 026; Ajay Jaiswal; Mingquan Lin; Sherry Zhuge; Yuzhe Yang 003; Dongkyun Kim; Trong-Hieu Nguyen Mau; Minh-Triet Tran; Jaehyup Jeong; Wongi Park; et al. (Medical Image Anal., 2024)

CancerGPT for few shot drug pair synergy prediction using large pretrained language models. - Tianhao Li; Sandesh Shetty; Advaith Kamath; Ajay Jaiswal; Xiaoqian Jiang; Ying Ding 001; Yejin Kim 001 (npj Digit. Medicine, 2024)

Bug severity prediction using LDA and sentiment scores: A CNN approach. - Ritu Bibyan; Sameer Anand; Ajay Jaiswal; Anu G. Aggarwal 001 (Expert Syst. J. Knowl. Eng., 2024)

Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients. - Zhenyu Zhang 015; Ajay Kumar Jaiswal; Lu Yin 006; Shiwei Liu 003; Jiawei Zhao; Yuandong Tian; Zhangyang Wang (CPAL, 2025)

SEBRA : Debiasing through Self-Guided Bias Ranking. - Adarsh Kappiyath; Abhra Chaudhuri; Ajay Kumar Jaiswal; Ziquan Liu; Yunpeng Li; Xiatian Zhu; Lu Yin 006 (ICLR, 2025)

Random permutation-based linear regression for cancelable biometrics. - Onkar Singh; Ajay Jaiswal; Nitin Kumar 001; Naveen Kumar (Expert Syst. J. Knowl. Eng., 2025)

IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model Pretraining. - Yixiao Li; Xianzhi Du; Ajay Jaiswal; Tao Lei; Tuo Zhao; Chong Wang; Jianyu Wang (CoRR, 2025)

Finding Fantastic Experts in MoEs: A Unified Study for Expert Dropping Strategies and Observations. - Ajay Jaiswal; Jianyu Wang; Yixiao Li; Pingzhi Li; Tianlong Chen 001; Zhangyang Wang; Chong Wang; Ruoming Pang; Xianzhi Du (CoRR, 2025)

Real-numbered singular matrix transformation for non-invertible and cancelable biometric templates. - Onkar Singh; Ajay Jaiswal; Naveen Kumar (Appl. Intell., 2025)

AlphaDecay: Module-wise Weight Decay for Heavy-Tailed Balancing in LLMs. - Di He; Ajay Jaiswal; Songjun Tu; Li Shen 008; Ganzhao Yuan; Shiwei Liu 003; Lu Yin 006 (CoRR, 2025)

Double-Checker: Enhancing Reasoning of Slow-Thinking LLMs via Self-Critical Fine-Tuning. - Xin Xu; Tianlong Chen 001; Fan Zhang; Wanlong Liu; Pengxiang Li; Ajay Kumar Jaiswal; Yuchen Yan; Jishan Hu; Yang Wang 020; Hao Chen; Shiwei Liu 003; Shizhe Diao; et al. (CoRR, 2025)

GPAS: Accelerating Convergence of LLM Pretraining via Gradient-Preserving Activation Scaling. - Tianlong Chen 001; Xin Xu; Zijing Liu; Pengxiang Li; Xinyuan Song; Ajay Kumar Jaiswal; Fan Zhang; Jishan Hu; Yang Wang 020; Hao Chen; Shizhe Diao; Shiwei Liu 003; et al. (CoRR, 2025)