Nikhil Mehta

According to our database, Nikhil Mehta authored at least 21 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Aligning Large Language Models with Recommendation Knowledge.

Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan H. Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy

CoRR, 2024

Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning.

Vinay Kumar Verma, Nikhil Mehta, Kevin J. Liang, Aakansha Mishra, Lawrence Carin

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings.

Nikhil Mehta, Kevin J. Liang, Jing Huang, Fu-Jen Chu, Li Yin, Tal Hassner

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Density Weighting for Multi-Interest Personalized Recommendation.

Nikhil Mehta, Anima Singh, Xinyang Yi, Sagar Jain, Lichan Hong, Ed H. Chi

CoRR, 2023

Better Generalization with Semantic IDs: A case study in Ranking for Recommendations.

Anima Singh, Trung Vu, Raghunandan H. Keshavan, Nikhil Mehta, Xinyang Yi, Lichan Hong, Lukasz Heldt, Li Wei, Ed H. Chi, Maheswaran Sathiamoorthy

CoRR, 2023

Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction.

Wang-Cheng Kang, Jianmo Ni, Nikhil Mehta, Maheswaran Sathiamoorthy, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng

CoRR, 2023

Pushing the Efficiency Limit Using Structured Sparse Convolutions.

Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Recommender Systems with Generative Retrieval.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Towards Efficient Continual Learning in Deep Neural Networks.

Nikhil Mehta

PhD thesis, 2022

Pseudo-OOD training for robust language models.

Dhanasekar Sundararaman, Nikhil Mehta, Lawrence Carin

CoRR, 2022

WAFFLe: Weight Anonymized Factorization for Federated Learning.

Weituo Hao, Nikhil Mehta, Kevin J. Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin

IEEE Access, 2022

2021

Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning.

Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Lawrence Carin

CoRR, 2021

Efficient Feature Transformations for Discriminative and Generative Continual Learning.

Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors.

Nikhil Mehta, Kevin J. Liang, Vinay Kumar Verma, Lawrence Carin

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Counterfactual Representation Learning with Balancing Weights.

Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Bayesian Nonparametric Weight Factorization for Continual Learning.

Nikhil Mehta, Kevin J. Liang, Lawrence Carin

CoRR, 2020

Survival cluster analysis.

Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao

Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Graph Representation Learning via Ladder Gamma Variational Autoencoders.

Arindam Sarkar, Nikhil Mehta, Piyush Rai

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Stochastic Blockmodels meet Graph Neural Networks.

Nikhil Mehta, Lawrence Carin, Piyush Rai

Proceedings of the 36th International Conference on Machine Learning, 2019

Deep Topic Models for Multi-label Learning.

Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Robust and Fast 3D Scan Alignment Using Mutual Information.

Nikhil Mehta, James R. McBride, Gaurav Pandey

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018