Nikhil Mehta

Orcid: 0009-0002-2928-7925

Affiliations:
  • Duke University, Durham, NC, USA (PhD 2020)
  • Google (former)
  • Meta (former)
  • IIT Kanpur, Department of Aerospace Engineering, India (former)


According to our database1, Nikhil Mehta authored at least 23 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2018
2019
2020
2021
2022
2023
2024
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
STAR: A Simple Training-free Approach for Recommendations using Large Language Models.
CoRR, 2024

Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Aligning Large Language Models with Recommendation Knowledge.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

2023
Density Weighting for Multi-Interest Personalized Recommendation.
CoRR, 2023

Better Generalization with Semantic IDs: A case study in Ranking for Recommendations.
CoRR, 2023

Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction.
CoRR, 2023

Pushing the Efficiency Limit Using Structured Sparse Convolutions.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Recommender Systems with Generative Retrieval.
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.
PhD thesis, 2022

Pseudo-OOD training for robust language models.
CoRR, 2022

WAFFLe: Weight Anonymized Factorization for Federated Learning.
IEEE Access, 2022

2021
Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning.
CoRR, 2021

Efficient Feature Transformations for Discriminative and Generative Continual Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Counterfactual Representation Learning with Balancing Weights.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Bayesian Nonparametric Weight Factorization for Continual Learning.
CoRR, 2020

Survival cluster analysis.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Graph Representation Learning via Ladder Gamma Variational Autoencoders.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Stochastic Blockmodels meet Graph Neural Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

Deep Topic Models for Multi-label Learning.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Robust and Fast 3D Scan Alignment Using Mutual Information.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018


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