Lokesh Nagalapatti

According to our database, Lokesh Nagalapatti authored at least 13 papers between 2019 and 2024.

Collaborative distances:

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

2024

Gradient Coreset for Federated Learning.

Durga Sivasubramanian, Lokesh Nagalapatti, Rishabh K. Iyer, Ganesh Ramakrishnan

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

PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect.

Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh, Sunita Sarawagi

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing.

Lokesh Nagalapatti, Akshay Iyer, Abir De, Sunita Sarawagi

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

A Data-centric AI Framework for Automating Exploratory Data Analysis and Data Quality Tasks.

Hima Patel, Shanmukha C. Guttula, Nitin Gupta, Sandeep Hans, Ruhi Sharma Mittal, Lokesh Nagalapatti

ACM J. Data Inf. Qual., December, 2023

2022

Learning Recourse on Instance Environment to Enhance Prediction Accuracy.

Lokesh Nagalapatti, Guntakanti Sai Koushik, Abir De, Sunita Sarawagi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Is Your Data Relevant?: Dynamic Selection of Relevant Data for Federated Learning.

Lokesh Nagalapatti, Ruhi Sharma Mittal, Ramasuri Narayanam

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Data Quality Toolkit: Automatic assessment of data quality and remediation for machine learning datasets.

Nitin Gupta, Hima Patel, Shazia Afzal, Naveen Panwar, Ruhi Sharma Mittal, Shanmukha C. Guttula, Abhinav Jain, Lokesh Nagalapatti, Sameep Mehta, Sandeep Hans, Pranay Lohia, Aniya Aggarwal, Diptikalyan Saha

CoRR, 2021

Data Augmentation for Fairness in Personal Knowledge Base Population.

Lingraj S. Vannur, Balaji Ganesan, Lokesh Nagalapatti, Hima Patel, M. N. Tippeswamy

Proceedings of the Trends and Applications in Knowledge Discovery and Data Mining, 2021

Ranking Data Slices for ML Model Validation: A Shapley Value Approach.

Eitan Farchi, Ramasuri Narayanam, Lokesh Nagalapatti

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Game of Gradients: Mitigating Irrelevant Clients in Federated Learning.

Lokesh Nagalapatti, Ramasuri Narayanam

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Data Augmentation for Personal Knowledge Graph Population.

Lingraj S. Vannur, Lokesh Nagalapatti, Balaji Ganesan, Hima Patel

CoRR, 2020

Overview and Importance of Data Quality for Machine Learning Tasks.

Abhinav Jain, Hima Patel, Lokesh Nagalapatti, Nitin Gupta, Sameep Mehta, Shanmukha C. Guttula, Shashank Mujumdar, Shazia Afzal, Ruhi Sharma Mittal, Vitobha Munigala

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

Outlier Aware Network Embedding for Attributed Networks.

Sambaran Bandyopadhyay, Lokesh Nagalapatti, M. Narasimha Murty

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019