Megha Khosla

According to our database, Megha Khosla authored at least 43 papers between 2013 and 2024.

Collaborative distances:

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

2024

DINE: Dimensional Interpretability of Node Embeddings.

Simone Piaggesi, Megha Khosla, André Panisson, Avishek Anand

IEEE Trans. Knowl. Data Eng., December, 2024

Efficient Neural Ranking Using Forward Indexes and Lightweight Encoders.

Jurek Leonhardt, Henrik Müller, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand

ACM Trans. Inf. Syst., September, 2024

AGALE: A Graph-Aware Continual Learning Evaluation Framework.

Tianqi Zhao, Alan Hanjalic, Megha Khosla

Trans. Mach. Learn. Res., 2024

Disentangled and Self-Explainable Node Representation Learning.

Simone Piaggesi, André Panisson, Megha Khosla

CoRR, 2024

A data-centric approach for assessing progress of Graph Neural Networks.

Tianqi Zhao, Ngan Thi Dong, Alan Hanjalic, Megha Khosla

CoRR, 2024

Model Selection with Model Zoo via Graph Learning.

Ziyu Li, Hilco van der Wilk, Danning Zhan, Megha Khosla, Alessandro Bozzon, Rihan Hai

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023

Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks.

Thorben Funke, Megha Khosla, Mandeep Rathee, Avishek Anand

IEEE Trans. Knowl. Data Eng., August, 2023

Private Graph Extraction via Feature Explanations.

Iyiola E. Olatunji, Mandeep Rathee, Thorben Funke, Megha Khosla

Proc. Priv. Enhancing Technol., April, 2023

Multi-label Node Classification On Graph-Structured Data.

Tianqi Zhao, Ngan Thi Dong, Alan Hanjalic, Megha Khosla

Trans. Mach. Learn. Res., 2023

Releasing Graph Neural Networks with Differential Privacy Guarantees.

Iyiola E. Olatunji, Thorben Funke, Megha Khosla

Trans. Mach. Learn. Res., 2023

Does Black-box Attribute Inference Attacks on Graph Neural Networks Constitute Privacy Risk?

Iyiola E. Olatunji, Anmar Hizber, Oliver Sihlovec, Megha Khosla

CoRR, 2023

2022

MuCoMiD: A Multitask Graph Convolutional Learning Framework for miRNA-Disease Association Prediction.

Ngan Dong, Stefanie Mücke, Megha Khosla

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Privacy and Transparency in Graph Machine Learning: A Unified Perspective.

Megha Khosla

CoRR, 2022

BAGEL: A Benchmark for Assessing Graph Neural Network Explanations.

Mandeep Rathee, Thorben Funke, Avishek Anand, Megha Khosla

CoRR, 2022

Efficient Neural Ranking using Forward Indexes.

Jurek Leonhardt, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

2021

A Comparative Study for Unsupervised Network Representation Learning.

Megha Khosla, Vinay Setty, Avishek Anand

IEEE Trans. Knowl. Data Eng., 2021

Fast Forward Indexes for Efficient Document Ranking.

Jurek Leonhardt, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand

CoRR, 2021

MuCoMiD: A Multitask Convolutional Learning Framework for miRNA-Disease Association Prediction.

Thi Ngan Dong, Megha Khosla

CoRR, 2021

Learnt Sparsification for Interpretable Graph Neural Networks.

Mandeep Rathee, Zijian Zhang, Thorben Funke, Megha Khosla, Avishek Anand

CoRR, 2021

Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks.

Thorben Funke, Megha Khosla, Avishek Anand

CoRR, 2021

Achieving differential privacy for k-nearest neighbors based outlier detection by data partitioning.

Jens Rauch, Iyiola E. Olatunji, Megha Khosla

CoRR, 2021

A Review of Anonymization for Healthcare Data.

Iyiola E. Olatunji, Jens Rauch, Matthias Katzensteiner, Megha Khosla

CoRR, 2021

Revisiting the Auction Algorithm for Weighted Bipartite Perfect Matchings.

Megha Khosla, Avishek Anand

CoRR, 2021

A multitask transfer learning framework for the prediction of virus-human protein-protein interactions.

Thi Ngan Dong, Graham Brogden, Gisa Gerold, Megha Khosla

BMC Bioinform., 2021

Membership Inference Attack on Graph Neural Networks.

Iyiola E. Olatunji, Wolfgang Nejdl, Megha Khosla

Proceedings of the 3rd IEEE International Conference on Trust, 2021

Extracting per Query Valid Explanations for Blackbox Learning-to-Rank Models.

Jaspreet Singh, Megha Khosla, Zhenye Wang, Avishek Anand

Proceedings of the ICTIR '21: The 2021 ACM SIGIR International Conference on the Theory of Information Retrieval, 2021

Knowledge-Aware Neural Networks for Medical Forum Question Classification.

Soumyadeep Roy, Sudip Chakraborty, Aishik Mandal, Gunjan Balde, Prakhar Sharma, Anandhavelu Natarajan, Megha Khosla, Shamik Sural, Niloy Ganguly

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Valid Explanations for Learning to Rank Models.

Jaspreet Singh, Megha Khosla, Avishek Anand

CoRR, 2020

Deep Reinforcement Learning with Graph-based State Representations.

Vikram Waradpande, Daniel Kudenko, Megha Khosla

CoRR, 2020

Boilerplate Removal using a Neural Sequence Labeling Model.

Jurek Leonhardt, Avishek Anand, Megha Khosla

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Towards a consistent evaluation of miRNA-disease association prediction models.

Thi Ngan Dong, Megha Khosla

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

Revisiting Feature Selection with Data Complexity.

Ngan Thi Dong, Megha Khosla

Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

2019

A Comprehensive Comparison of Unsupervised Network Representation Learning Methods.

Megha Khosla, Avishek Anand, Vinay Setty

CoRR, 2019

Estimating PageRank deviations in crawled graphs.

Helge Holzmann, Avishek Anand, Megha Khosla

Appl. Netw. Sci., 2019

A Faster Algorithm for Cuckoo Insertion and Bipartite Matching in Large Graphs.

Megha Khosla, Avishek Anand

Algorithmica, 2019

Asynchronous Training of Word Embeddings for Large Text Corpora.

Avishek Anand, Megha Khosla, Jaspreet Singh, Jan-Hendrik Zab, Zijian Zhang

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Node Representation Learning for Directed Graphs.

Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl, Avishek Anand

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Finding Interpretable Concept Spaces in Node Embeddings Using Knowledge Bases.

Maximilian Idahl, Megha Khosla, Avishek Anand

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

2018

User Fairness in Recommender Systems.

Jurek Leonhardt, Avishek Anand, Megha Khosla

Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Delusive PageRank in Incomplete Graphs.

Helge Holzmann, Avishek Anand, Megha Khosla

Proceedings of the Complex Networks and Their Applications VII, 2018

2016

The Multiple-Orientability Thresholds for Random Hypergraphs.

Nikolaos Fountoulakis, Megha Khosla, Konstantinos Panagiotou

Comb. Probab. Comput., 2016

2014

Multiple choice allocations with small maximum loads.

Megha Khosla

PhD thesis, 2014

2013

Balls into Bins Made Faster.

Megha Khosla

Proceedings of the Algorithms - ESA 2013, 2013