Disha Makhija - RankMe

18 papers A* 3A 2Journal 11Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Neural Breadcrumbs: Membership Inference Attacks on LLMs Through Hidden State and Attention Pattern Analysis. EACL (Volume 1: Long Papers) Disha Makhija, Manoj Ghuhan Arivazhagan, Vinayshekhar Bannihatti Kumar, Rashmi Gangadharaiah
2025	J	`jnl`	Neural Breadcrumbs: Membership Inference Attacks on LLMs Through Hidden State and Attention Pattern Analysis. CoRR Disha Makhija, Manoj Ghuhan Arivazhagan, Vinayshekhar Bannihatti Kumar, Rashmi Gangadharaiah
2024	A*	`conf`	A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings. NeurIPS Disha Makhija, Joydeep Ghosh, Nhat Ho
2024	J	`jnl`	Achieving Fairness Across Local and Global Models in Federated Learning. CoRR Disha Makhija, Xing Han, Joydeep Ghosh, Yejin Kim
2024	J	`jnl`	Federated Learning for Estimating Heterogeneous Treatment Effects. CoRR Disha Makhija, Joydeep Ghosh, Yejin Kim
2023	J	`jnl`	Privacy Preserving Bayesian Federated Learning in Heterogeneous Settings. CoRR Disha Makhija, Joydeep Ghosh, Nhat Ho
2022	A*	`conf`	Architecture Agnostic Federated Learning for Neural Networks. ICML Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh
2022	J	`jnl`	Architecture Agnostic Federated Learning for Neural Networks. CoRR Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh
2022	J	`jnl`	Federated Self-supervised Learning for Heterogeneous Clients. CoRR Disha Makhija, Nhat Ho, Joydeep Ghosh
2020	J	`jnl`	Audience Creation for Consumables - Simple and Scalable Precision Merchandising for a Growing Marketplace. CoRR Shreyas Sheshadri, Harsh Maheshwari, Avijit Saha, Samik Datta, Shashank Jain, Disha Makhija, Anuj Nagpal, Sneha Shukla, Suyash S
2020	A*	`conf`	Understanding the Success of Graph-based Semi-Supervised Learning using Partially Labelled Stochastic Block Model. IJCAI Avirup Saha, Shreyas Sheshadri, Samik Datta, Niloy Ganguly, Disha Makhija, Priyank Patel
2018	A	`conf`	REV2: Fraudulent User Prediction in Rating Platforms. WSDM Srijan Kumar, Bryan Hooi, Disha Makhija, Mohit Kumar, Christos Faloutsos, V. S. Subrahmanian
2017	J	`jnl`	FairJudge: Trustworthy User Prediction in Rating Platforms. CoRR Srijan Kumar, Bryan Hooi, Disha Makhija, Mohit Kumar, Christos Faloutsos, V. S. Subrahmanian
2017	J	`jnl`	ZooBP: Belief Propagation for Heterogeneous Networks. Proc. VLDB Endow. Dhivya Eswaran, Stephan Günnemann, Christos Faloutsos, Disha Makhija, Mohit Kumar
2016	A	`conf`	BIRDNEST: Bayesian Inference for Ratings-Fraud Detection. SDM Bryan Hooi, Neil Shah, Alex Beutel, Stephan Günnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos
2016	—	`conf`	EdgeCentric: Anomaly Detection in Edge-Attributed Networks. ICDM Workshops Neil Shah, Alex Beutel, Bryan Hooi, Leman Akoglu, Stephan Günnemann, Disha Makhija, Mohit Kumar, Christos Faloutsos
2015	J	`jnl`	BIRDNEST: Bayesian Inference for Ratings-Fraud Detection. CoRR Bryan Hooi, Neil Shah, Alex Beutel, Stephan Günnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos
2015	J	`jnl`	EdgeCentric: Anomaly Detection in Edge-Attributed Networks. CoRR Neil Shah, Alex Beutel, Bryan Hooi, Leman Akoglu, Stephan Günnemann, Disha Makhija, Mohit Kumar, Christos Faloutsos