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ORCIDAjay Jaiswal
Ajay Kumar Jaiswal
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2020 – today
- 2024
[j13]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)- [j12]Sameer Anand, Ajay Jaiswal, Vibha Verma, Atul Singh:
Modeling the impact of noise and uncertain operational environment on software release decisions considering testing coverage-based SRGM. Intell. Decis. Technol. 18(3): 2339-2352 (2024) - [j11]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: 103224 (2024) - [j10]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) - [c37]Ajay Jaiswal, Bodun Hu, Lu Yin, Yeonju Ro, Tianlong Chen, Shiwei Liu, Aditya Akella:
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. EMNLP 2024: 16943-16956 - [c36]Abhinav Bandari, Lu Yin, Cheng-Yu Hsieh, Ajay Jaiswal, Tianlong Chen, Li Shen, Ranjay Krishna, Shiwei Liu:
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning. EMNLP 2024: 18089-18099 - [c35]Ajay Kumar Jaiswal, Zhe Gan, Xianzhi Du, Bowen Zhang, Zhangyang Wang, Yinfei Yang:
Compressing LLMs: The Truth is Rarely Pure and Never Simple. ICLR 2024 - [c34]Lu Yin, Ajay Kumar Jaiswal, Shiwei Liu, Souvik Kundu, Zhangyang Wang:
Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs. ICML 2024 - [c33]Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Gen Li, Ajay Kumar Jaiswal, Mykola Pechenizkiy, Yi Liang, Michael Bendersky, Zhangyang Wang, Shiwei Liu:
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. ICML 2024 - [c32]Runjin Chen, Tong Zhao, Ajay Kumar Jaiswal, Neil Shah, Zhangyang Wang:
LLaGA: Large Language and Graph Assistant. ICML 2024 - [c31]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, Dawn Song, Zhangyang Wang, Bo Li:
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression. ICML 2024 - [c30]Zhangheng Li, Shiwei Liu, Tianlong Chen, Ajay Kumar Jaiswal, Zhenyu Zhang, Dilin Wang, Raghuraman Krishnamoorthi, Shiyu Chang, Zhangyang Wang:
Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once. ICML 2024 - [c29]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: 6215-6224 - [i33]Runjin Chen, Tong Zhao, Ajay Jaiswal, Neil Shah, Zhangyang Wang:
LLaGA: Large Language and Graph Assistant. CoRR abs/2402.08170 (2024) - [i32]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 abs/2403.15447 (2024) - [i31]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 abs/2404.03865 (2024) - [i30]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 abs/2407.08296 (2024) - [i29]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 abs/2407.11239 (2024) - [i28]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 abs/2407.14996 (2024) - [i27]Abhinav Bandari, Lu Yin, Cheng-Yu Hsieh, Ajay Kumar Jaiswal, Tianlong Chen, Li Shen, Ranjay Krishna, Shiwei Liu:
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning. CoRR abs/2410.07461 (2024) - [i26]Awais Naeem, Tianhao Li, Huang-Ru Liao, Jiawei Xu, Aby M. Mathew, Zehao Zhu, Zhen Tan, Ajay Kumar Jaiswal, Raffi A. Salibian, Ziniu Hu, Tianlong Chen, Ying Ding:
Path-RAG: Knowledge-Guided Key Region Retrieval for Open-ended Pathology Visual Question Answering. CoRR abs/2411.17073 (2024) - 2023
- [j9]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): 126-133 (2023) - [c28]Ajay Jaiswal, Xingguang Zhang, Stanley H. Chan, Zhangyang Wang:
Physics-Driven Turbulence Image Restoration with Stochastic Refinement. ICCV 2023: 12136-12147 - [c27]Tianlong Chen, Zhenyu Zhang, Ajay Kumar Jaiswal, Shiwei Liu, Zhangyang Wang:
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. ICLR 2023 - [c26]Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang:
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! ICLR 2023 - [c25]Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. ICML 2023: 14679-14690 - [c24]Ajay Kumar 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. ICML 2023: 14691-14701 - [c23]Wenqing Zheng, S. P. Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang:
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation. ICML 2023: 42403-42419 - [c22]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: 331-339 - [c21]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: 663-673 - [c20]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang:
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. NeurIPS 2023 - [c19]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: 4976-4985 - [i25]Tianlong Chen, Zhenyu Zhang, Ajay Jaiswal, Shiwei Liu, Zhangyang Wang:
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. CoRR abs/2303.01610 (2023) - [i24]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 abs/2303.02141 (2023) - [i23]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. CoRR abs/2303.02473 (2023) - [i22]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 abs/2304.10946 (2023) - [i21]Wenqing Zheng, S. P. Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang:
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation. CoRR abs/2305.00909 (2023) - [i20]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang:
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. CoRR abs/2306.03805 (2023) - [i19]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 abs/2306.10460 (2023) - [i18]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. CoRR abs/2306.10466 (2023) - [i17]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 abs/2306.17206 (2023) - [i16]Ajay Jaiswal, Xingguang Zhang, Stanley H. Chan, Zhangyang Wang:
Physics-Driven Turbulence Image Restoration with Stochastic Refinement. CoRR abs/2307.10603 (2023) - [i15]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 abs/2308.09180 (2023) - [i14]Ajay Jaiswal, Zhe Gan, Xianzhi Du, Bowen Zhang, Zhangyang Wang, Yinfei Yang:
Compressing LLMs: The Truth is Rarely Pure and Never Simple. CoRR abs/2310.01382 (2023) - [i13]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 abs/2310.02277 (2023) - [i12]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 abs/2310.16112 (2023) - 2022
- [j8]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): 101295 (2022) - [j7]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): 101337 (2022) - [j6]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): 34573-34593 (2022) - [c18]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: 430-446 - [c17]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: 981-986 - [c16]Ajay Kumar Jaiswal, Haoyu Ma, Tianlong Chen, Ying Ding, Zhangyang Wang:
Training Your Sparse Neural Network Better with Any Mask. ICML 2022: 9833-9844 - [c15]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 - [i11]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 abs/2205.08756 (2022) - [i10]Ajay Jaiswal, Haoyu Ma, Tianlong Chen, Ying Ding, Zhangyang Wang:
Training Your Sparse Neural Network Better with Any Mask. CoRR abs/2206.12755 (2022) - [i9]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 abs/2207.10040 (2022) - [i8]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 abs/2210.08122 (2022) - [i7]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 abs/2210.08388 (2022) - [i6]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 abs/2212.02675 (2022) - 2021
- [c14]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 - [c13]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: 1132-1137 - [c12]Ajay Jaiswal, Meijun Liu, Ying Ding:
Understanding Parachuting Collaboration. iConference (1) 2021: 183-189 - [c11]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: 196-208 - [i5]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 abs/2110.14787 (2021) - [i4]Ajay Jaiswal, Liyan Tang, Meheli Ghosh, Justin F. Rousseau, Yifan Peng, Ying Ding:
RadBERT-CL: Factually-Aware Contrastive Learning For Radiology Report Classification. CoRR abs/2110.15426 (2021) - 2020
- [j5]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): 63-83 (2020) - [c10]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: 585-593 - [c9]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: 1802-1807 - [i3]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 abs/2009.07473 (2020) - [i2]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 abs/2011.12506 (2020)
2010 – 2019
- 2017
- [c8]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: 59-68 - [e1]Ajay Jaiswal, Vijender Kumar Solanki, Zhongyu (Joan) Lu, Nikhil Rajput:
Proceedings of the First International Conference on Information Technology and Knowledge Management, New Delhi, India, December 22-23, 2017. Annals of Computer Science and Information Systems 14, 2017, ISBN 978-83-949419-2-5 [contents] - [i1]Mayank Singh, Ajay Jaiswal, Priya Shree, Arindam Pal, Animesh Mukherjee, Pawan Goyal:
Understanding the Impact of Early Citers on Long-Term Scientific Impact. CoRR abs/1705.03178 (2017) - 2016
- [j4]Nitin Kumar, Ramesh K. Agrawal, Ajay Jaiswal:
Incremental and Decremental Nonparametric Discriminant Analysis for Face Recognition. Comput. Informatics 35(5): 1231-1248 (2016) - [c7]Nitin Kumar, Maheep Singh, Mahesh Chandra Govil, Emmanuel S. Pilli, Ajay Jaiswal:
Salient Object Detection in Noisy Images. Canadian AI 2016: 109-114 - 2015
- [j3]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): 24-45 (2015) - 2014
- [j2]Nitin Kumar, R. K. Agrawal, Ajay Jaiswal:
Incremental and Decremental Exponential Discriminant Analysis for Face Recognition. Int. J. Comput. Vis. Image Process. 4(1): 40-55 (2014) - [c6]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: 23-32 - 2012
- [j1]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): 48-58 (2012) - [c5]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: 77-86 - [c4]Ajay Jaiswal, Nitin Kumar, Ramesh K. Agrawal:
A Hybrid of Principal Component Analysis and Partial Least Squares for Face Recognition across Pose. CIARP 2012: 67-73 - [c3]Nitin Kumar, Ajay Jaiswal, Ramesh K. Agrawal:
Performance evaluation of subspace methods to tackle small sample size problem in face recognition. ICACCI 2012: 938-944 - [c2]Ajay Jaiswal, Nitin Kumar, R. K. Agrawal:
Statistical Framework for Facial Pose Classification. MICAI (1) 2012: 87-96 - 2011
- [c1]Ajay Jaiswal, Ramesh K. Agrawal, Nitin Kumar:
Performance evaluation of linear subspace methods for face recognition under illumination variation. C3S2E 2011: 103-110
Coauthor Index
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