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2020 – today
- 2024
[c20]Vidit Jain, Mukund Rungta, Yuchen Zhuang, Yue Yu, Zeyu Wang, Mu Gao, Jeffrey Skolnick, Chao Zhang:
HiGen: Hierarchy-Aware Sequence Generation for Hierarchical Text Classification. EACL (1) 2024: 1354-1368- [c19]Anirudh Buvanesh, Rahul Chand, Jatin Prakash, Bhawna Paliwal, Mudit Dhawan, Neelabh Madan, Deepesh Hada, Vidit Jain, Sonu Mehta, Yashoteja Prabhu, Manish Gupta, Ramachandran Ramjee, Manik Varma:
Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction. ICLR 2024 - [i4]Vidit Jain, Mukund Rungta, Yuchen Zhuang, Yue Yu, Zeyu Wang, Mu Gao, Jeffrey Skolnick, Chao Zhang:
HiGen: Hierarchy-Aware Sequence Generation for Hierarchical Text Classification. CoRR abs/2402.01696 (2024) - 2023
- [c18]Vidit Jain, Jatin Prakash, Deepak Saini, Jian Jiao, Ramachandran Ramjee, Manik Varma:
Renee: End-To-End Training of Extreme Classification Models. MLSys 2023 - [c17]Kunal Dahiya
, Nilesh Gupta, Deepak Saini, Akshay Soni, Yajun Wang, Kushal Dave, Jian Jiao, Gururaj K, Prasenjit Dey, Amit Singh, Deepesh Hada, Vidit Jain, Bhawna Paliwal, Anshul Mittal, Sonu Mehta, Ramachandran Ramjee, Sumeet Agarwal, Purushottam Kar, Manik Varma:
NGAME: Negative Mining-aware Mini-batching for Extreme Classification. WSDM 2023: 258-266 - 2022
- [j2]Vidit Jain, Rohit Kumar Kaliyar, Anurag Goswami, Pratik Narang, Yashvardhan Sharma:
AENeT: an attention-enabled neural architecture for fake news detection using contextual features. Neural Comput. Appl. 34(1): 771-782 (2022) - [c16]Yatin Nandwani, Vidit Jain, Mausam, Parag Singla:
Neural Models for Output-Space Invariance in Combinatorial Problems. ICLR 2022 - [i3]Yatin Nandwani, Vidit Jain, Mausam, Parag Singla:
Neural Models for Output-Space Invariance in Combinatorial Problems. CoRR abs/2202.03229 (2022) - [i2]Kunal Dahiya, Nilesh Gupta, Deepak Saini, Akshay Soni, Yajun Wang, Kushal Dave, Jian Jiao, Gururaj K, Prasenjit Dey, Amit Singh, Deepesh Hada, Vidit Jain, Bhawna Paliwal, Anshul Mittal, Sonu Mehta, Ramachandran Ramjee, Sumeet Agarwal, Purushottam Kar, Manik Varma:
NGAME: Negative Mining-aware Mini-batching for Extreme Classification. CoRR abs/2207.04452 (2022) - 2021
- [c15]Vidit Jain, Maitree Leekha, Rajiv Ratn Shah, Jainendra Shukla:
Exploring Semi-Supervised Learning for Predicting Listener Backchannels. CHI 2021: 395:1-395:12 - [i1]Vidit Jain, Maitree Leekha, Rajiv Ratn Shah, Jainendra Shukla:
Exploring Semi-Supervised Learning for Predicting Listener Backchannels. CoRR abs/2101.01899 (2021) - 2020
- [c14]Aanchal Mongia, Vidit Jain, Angshul Majumdar:
Deep Matrix Factorization on Graphs: Application to Collaborative Filtering. ICONIP (4) 2020: 754-762
2010 – 2019
- 2019
- [c13]Aanchal Mongia, Vidit Jain, Emilie Chouzenoux, Angshul Majumdar:
Deep Latent Factor Model for Predicting Drug Target Interactions. ICASSP 2019: 1254-1258 - 2015
- [j1]Sainyam Galhotra, Amitabha Bagchi, Srikanta Bedathur, Maya Ramanath, Vidit Jain:
Tracking the Conductance of Rapidly Evolving Topic-Subgraphs. Proc. VLDB Endow. 8(13): 2170-2181 (2015) - 2014
- [c12]Vidit Jain, Sainyam Galhotra:
Min-d-Occur: Ensuring Future Occurrences in Streaming Sets. UAI 2014: 370-379 - [c11]Vidit Jain, Jay Mahadeokar:
Short-text representation using diffusion wavelets. WWW (Companion Volume) 2014: 301-302 - 2013
- [c10]Vidit Jain, Sachin Sudhakar Farfade:
Adapting Classification Cascades to New Domains. ICCV 2013: 105-112 - [c9]Vidit Jain, Esther Galbrun:
Topical organization of user comments and application to content recommendation. WWW (Companion Volume) 2013: 61-62 - 2011
- [c8]Vidit Jain, Erik G. Learned-Miller:
Online domain adaptation of a pre-trained cascade of classifiers. CVPR 2011: 577-584 - [c7]Vidit Jain, Manik Varma:
Learning to re-rank: query-dependent image re-ranking using click data. WWW 2011: 277-286
2000 – 2009
- 2008
- [c6]Vidit Jain, Amit Singhal, Jiebo Luo:
Selective hidden random fields: Exploiting domain-specific saliency for event classification. CVPR 2008 - 2007
- [c5]Gary B. Huang, Vidit Jain, Erik G. Learned-Miller:
Unsupervised Joint Alignment of Complex Images. ICCV 2007: 1-8 - [c4]Vidit Jain, Erik G. Learned-Miller, Andrew McCallum:
People-LDA: Anchoring Topics to People using Face Recognition. ICCV 2007: 1-8 - 2006
- [c3]Vidit Jain, Andras Ferencz, Erik G. Learned-Miller:
Discriminative Training of Hyper-feature Models for Object Identification. BMVC 2006: 357-366 - 2005
- [c2]Erik G. Learned-Miller, Vidit Jain:
Many Heads Are Better Than One: Jointly Removing Bias from Multiple MRIs Using Nonparametric Maximum Likelihood. IPMI 2005: 615-626 - 2002
- [c1]Marghoob Mohiyuddin, Vidit Jain, Phalguni Gupta:
Parallel Bi-dimensional Pattern Matching with Scaling. IASTED PDCS 2002: 117-122
Coauthor Index
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