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ORCIDNikhil Mehta 0002
Person information
- affiliation (PhD 2020): Duke University, Durham, NC, USA
- affiliation (former): Google
- affiliation (former): Meta
- affiliation (former): IIT Kanpur, Department of Aerospace Engineering, India
Other persons with the same name
- Nikhil Mehta 0001 — University of North Carolina Greensboro, School of Business and Economics, NC, USA (and 3 more)
- Nikhil Mehta 0003 — Purdue University, Department of Computer Science, West Lafayette, IN, USA
- Nikhil Mehta 0004
![[0000-0002-7277-8466]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-7277-8466")
— NVIDIA, USA (and 1 more) - Nikhil Mehta 0005 — Columbia University, Department of Computer Science, New York, NY, USA
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Books and Theses
- 2022
[b1]Nikhil Mehta:
Towards Efficient Continual Learning in Deep Neural Networks. Duke University, Durham, NC, USA, 2022
Journal Articles
- 2022
- [j1]Weituo Hao, Nikhil Mehta, Kevin J. Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin:
WAFFLe: Weight Anonymized Factorization for Federated Learning. IEEE Access 10: 49207-49218 (2022)
Conference and Workshop Papers
- 2024
- [c13]Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan Hulikal Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy:
Aligning Large Language Models with Recommendation Knowledge. NAACL-HLT (Findings) 2024: 1051-1066 - [c12]Nikhil Mehta, Kevin J. Liang, Jing Huang, Fu-Jen Chu, Li Yin, Tal Hassner:
HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings. WACV 2024: 2399-2409 - [c11]Vinay Kumar Verma, Nikhil Mehta, Kevin J. Liang, Aakansha Mishra, Lawrence Carin:
Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning. WACV 2024: 2709-2719 - 2023
- [c10]Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Mahesh Sathiamoorthy:
Recommender Systems with Generative Retrieval. NeurIPS 2023 - [c9]Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin:
Pushing the Efficiency Limit Using Structured Sparse Convolutions. WACV 2023: 6492-6502 - 2021
- [c8]Nikhil Mehta, Kevin J. Liang, Vinay Kumar Verma, Lawrence Carin:
Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors. AISTATS 2021: 100-108 - [c7]Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin:
Counterfactual Representation Learning with Balancing Weights. AISTATS 2021: 1972-1980 - [c6]Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin:
Efficient Feature Transformations for Discriminative and Generative Continual Learning. CVPR 2021: 13865-13875 - 2020
- [c5]Arindam Sarkar, Nikhil Mehta, Piyush Rai:
Graph Representation Learning via Ladder Gamma Variational Autoencoders. AAAI 2020: 5604-5611 - [c4]Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao:
Survival cluster analysis. CHIL 2020: 60-68 - 2019
- [c3]Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai:
Deep Topic Models for Multi-label Learning. AISTATS 2019: 2849-2857 - [c2]Nikhil Mehta, Lawrence Carin, Piyush Rai:
Stochastic Blockmodels meet Graph Neural Networks. ICML 2019: 4466-4474 - 2018
- [c1]Nikhil Mehta, James R. McBride, Gaurav Pandey:
Robust and Fast 3D Scan Alignment Using Mutual Information. ICRA 2018: 1-8
Informal and Other Publications
- 2024
- [i17]Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan H. Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy:
Aligning Large Language Models with Recommendation Knowledge. CoRR abs/2404.00245 (2024) - 2023
- [i16]Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan H. Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Maheswaran Sathiamoorthy:
Recommender Systems with Generative Retrieval. CoRR abs/2305.05065 (2023) - [i15]Wang-Cheng Kang, Jianmo Ni, Nikhil Mehta, Maheswaran Sathiamoorthy, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. CoRR abs/2305.06474 (2023) - [i14]Anima Singh, Trung Vu, Raghunandan H. Keshavan, Nikhil Mehta, Xinyang Yi, Lichan Hong, Lukasz Heldt, Li Wei, Ed H. Chi, Maheswaran Sathiamoorthy:
Better Generalization with Semantic IDs: A case study in Ranking for Recommendations. CoRR abs/2306.08121 (2023) - [i13]Nikhil Mehta, Anima Singh, Xinyang Yi, Sagar Jain, Lichan Hong, Ed H. Chi:
Density Weighting for Multi-Interest Personalized Recommendation. CoRR abs/2308.01563 (2023) - [i12]Vinay Kumar Verma, Nikhil Mehta, Kevin J. Liang, Aakansha Mishra, Lawrence Carin:
Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning. CoRR abs/2312.01167 (2023) - [i11]Nikhil Mehta, Kevin J. Liang, Jing Huang, Fu-Jen Chu, Li Yin, Tal Hassner:
HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings. CoRR abs/2312.15086 (2023) - 2022
- [i10]Dhanasekar Sundararaman, Nikhil Mehta, Lawrence Carin:
Pseudo-OOD training for robust language models. CoRR abs/2210.09132 (2022) - [i9]Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin:
Pushing the Efficiency Limit Using Structured Sparse Convolutions. CoRR abs/2210.12818 (2022) - 2021
- [i8]Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Lawrence Carin:
Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning. CoRR abs/2102.11856 (2021) - [i7]Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin:
Efficient Feature Transformations for Discriminative and Generative Continual Learning. CoRR abs/2103.13558 (2021) - 2020
- [i6]Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao:
Survival Cluster Analysis. CoRR abs/2003.00355 (2020) - [i5]Nikhil Mehta, Kevin J. Liang, Lawrence Carin:
Bayesian Nonparametric Weight Factorization for Continual Learning. CoRR abs/2004.10098 (2020) - [i4]Weituo Hao, Nikhil Mehta, Kevin J. Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin:
WAFFLe: Weight Anonymized Factorization for Federated Learning. CoRR abs/2008.05687 (2020) - [i3]Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin:
Counterfactual Representation Learning with Balancing Weights. CoRR abs/2010.12618 (2020) - 2019
- [i2]Nikhil Mehta, Lawrence Carin, Piyush Rai:
Stochastic Blockmodels meet Graph Neural Networks. CoRR abs/1905.05738 (2019) - 2017
- [i1]Nikhil Mehta, James R. McBride, Gaurav Pandey:
Robust and Fast 3D Scan Alignment using Mutual Information. CoRR abs/1709.06948 (2017)
Coauthor Index
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