Disha Makhija

According to our database, Disha Makhija authored at least 16 papers between 2016 and 2026.

Collaborative distances:

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

2026

Probing the Prompt KV Cache: Where It Becomes Dispensable.

Vinayshekhar Bannihatti Kumar, Manoj Ghuhan Arivazhagan, Disha Makhija, Rashmi Gangadharaiah

CoRR, May, 2026

Syntax Without Semantics: Teaching Large Language Models to Code in an Unseen Language.

Vinayshekhar Bannihatti Kumar, Disha Makhija, Manoj Ghuhan Arivazhagan, Rashmi Gangadharaiah

CoRR, May, 2026

Neural Breadcrumbs: Membership Inference Attacks on LLMs Through Hidden State and Attention Pattern Analysis.

Disha Makhija, Manoj Ghuhan Arivazhagan, Vinayshekhar Bannihatti Kumar, Rashmi Gangadharaiah

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

2024

Achieving Fairness Across Local and Global Models in Federated Learning.

Disha Makhija, Xing Han, Joydeep Ghosh, Yejin Kim

CoRR, 2024

Federated Learning for Estimating Heterogeneous Treatment Effects.

Disha Makhija, Joydeep Ghosh, Yejin Kim

CoRR, 2024

A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings.

Disha Makhija, Joydeep Ghosh, Nhat Ho

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Privacy Preserving Bayesian Federated Learning in Heterogeneous Settings.

Disha Makhija, Joydeep Ghosh, Nhat Ho

CoRR, 2023

2022

Federated Self-supervised Learning for Heterogeneous Clients.

Disha Makhija, Nhat Ho, Joydeep Ghosh

CoRR, 2022

Architecture Agnostic Federated Learning for Neural Networks.

Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh

Proceedings of the International Conference on Machine Learning, 2022

2020

Audience Creation for Consumables - Simple and Scalable Precision Merchandising for a Growing Marketplace.

Shreyas Sheshadri, Harsh Maheshwari, Avijit Saha, Samik Datta, Shashank Jain, Disha Makhija, Anuj Nagpal, Sneha Shukla, Suyash S

CoRR, 2020

Understanding the Success of Graph-based Semi-Supervised Learning using Partially Labelled Stochastic Block Model.

Avirup Saha, Shreyas Sheshadri, Samik Datta, Niloy Ganguly, Disha Makhija, Priyank Patel

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2018

REV2: Fraudulent User Prediction in Rating Platforms.

Srijan Kumar, Bryan Hooi, Disha Makhija, Mohit Kumar, Christos Faloutsos, V. S. Subrahmanian

Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

2017

ZooBP: Belief Propagation for Heterogeneous Networks.

Dhivya Eswaran, Stephan Günnemann, Christos Faloutsos, Disha Makhija, Mohit Kumar

Proc. VLDB Endow., 2017

FairJudge: Trustworthy User Prediction in Rating Platforms.

Srijan Kumar, Bryan Hooi, Disha Makhija, Mohit Kumar, Christos Faloutsos, V. S. Subrahmanian

CoRR, 2017

2016

BIRDNEST: Bayesian Inference for Ratings-Fraud Detection.

Bryan Hooi, Neil Shah, Alex Beutel, Stephan Günnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

EdgeCentric: Anomaly Detection in Edge-Attributed Networks.

Neil Shah, Alex Beutel, Bryan Hooi, Leman Akoglu, Stephan Günnemann, Disha Makhija, Mohit Kumar, Christos Faloutsos

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016