Megha Khosla - RankMe

70 papers A* 3A 3C 1Misc 1Journal 54Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	How does Graph Structure Modulate Membership-Inference Risk for Graph Neural Networks? CoRR Megha Khosla
2026	J	`jnl`	Multi-Source Transfer Learning With Spatial-Temporal Graph Neural Network for Short-Term Bicycle Traffic Prediction. IEEE Trans. Intell. Transp. Syst. Xiamei Wen, Megha Khosla, Serge P. Hoogendoorn
2026	J	`jnl`	Towards unbiased action value estimation in reinforcement learning. Neurocomputing Yuan Xue, Daniel Kudenko, Megha Khosla
2025	J	`jnl`	Disentangled and Self-Explainable Node Representation Learning. Trans. Mach. Learn. Res. Simone Piaggesi, André Panisson, Megha Khosla
2025	J	`jnl`	Draw a Portrait of Your Graph Data: An Instance-Level Profiling Framework for Graph-Structured Data. CoRR Tianqi Zhao, Russa Biswas, Megha Khosla
2025	J	`jnl`	Graph learning-based generation of abstractions for reinforcement learning. Neural Comput. Appl. Yuan Xue, Daniel Kudenko, Megha Khosla
2025	J	`jnl`	Population-Scale Network Embeddings Expose Educational Divides in Network Structure Related to Right-Wing Populist Voting. CoRR Malte Lüken, Javier Garcia-Bernardo, Sreeparna Deb, Flavio Hafner, Megha Khosla
2024	J	`jnl`	A Review of Anonymization for Healthcare Data. Big Data Iyiola E. Olatunji, Jens Rauch, Matthias Katzensteiner, Megha Khosla
2024	J	`jnl`	A data-centric approach for assessing progress of Graph Neural Networks. CoRR Tianqi Zhao, Ngan Thi Dong, Alan Hanjalic, Megha Khosla
2024	J	`jnl`	AGALE: A Graph-Aware Continual Learning Evaluation Framework. CoRR Tianqi Zhao, Alan Hanjalic, Megha Khosla
2024	J	`jnl`	AGALE: A Graph-Aware Continual Learning Evaluation Framework. Trans. Mach. Learn. Res. Tianqi Zhao, Alan Hanjalic, Megha Khosla
2024	J	`jnl`	DINE: Dimensional Interpretability of Node Embeddings. IEEE Trans. Knowl. Data Eng. Simone Piaggesi, Megha Khosla, André Panisson, Avishek Anand
2024	J	`jnl`	Disentangled and Self-Explainable Node Representation Learning. CoRR Simone Piaggesi, André Panisson, Megha Khosla
2024	J	`jnl`	Efficient Neural Ranking Using Forward Indexes and Lightweight Encoders. ACM Trans. Inf. Syst. Jurek Leonhardt, Henrik Müller, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand
2024	J	`jnl`	GNN-MultiFix: Addressing the pitfalls for GNNs for multi-label node classification. CoRR Tianqi Zhao, Megha Khosla
2024	A*	`conf`	Model Selection with Model Zoo via Graph Learning. ICDE Ziyu Li, Hilco van der Wilk, Danning Zhan, Megha Khosla, Alessandro Bozzon, Rihan Hai
2024	J	`jnl`	Model Selection with Model Zoo via Graph Learning. CoRR Ziyu Li, Hilco van der Wilk, Danning Zhan, Megha Khosla, Alessandro Bozzon, Rihan Hai
2023	J	`jnl`	DINE: Dimensional Interpretability of Node Embeddings. CoRR Simone Piaggesi, Megha Khosla, André Panisson, Avishek Anand
2023	J	`jnl`	Does Black-box Attribute Inference Attacks on Graph Neural Networks Constitute Privacy Risk? CoRR Iyiola E. Olatunji, Anmar Hizber, Oliver Sihlovec, Megha Khosla
2023	J	`jnl`	Efficient Neural Ranking using Forward Indexes and Lightweight Encoders. CoRR Jurek Leonhardt, Henrik Müller, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand
2023	J	`jnl`	Multi-label Node Classification On Graph-Structured Data. CoRR Tianqi Zhao, Ngan Thi Dong, Alan Hanjalic, Megha Khosla
2023	J	`jnl`	Multi-label Node Classification On Graph-Structured Data. Trans. Mach. Learn. Res. Tianqi Zhao, Ngan Thi Dong, Alan Hanjalic, Megha Khosla
2023	J	`jnl`	Private Graph Extraction via Feature Explanations. Proc. Priv. Enhancing Technol. Iyiola E. Olatunji, Mandeep Rathee, Thorben Funke, Megha Khosla
2023	J	`jnl`	Releasing Graph Neural Networks with Differential Privacy Guarantees. Trans. Mach. Learn. Res. Iyiola E. Olatunji, Thorben Funke, Megha Khosla
2023	J	`jnl`	Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks. IEEE Trans. Knowl. Data Eng. Thorben Funke, Megha Khosla, Mandeep Rathee, Avishek Anand
2022	J	`jnl`	BAGEL: A Benchmark for Assessing Graph Neural Network Explanations. CoRR Mandeep Rathee, Thorben Funke, Avishek Anand, Megha Khosla
2022	A*	`conf`	Efficient Neural Ranking using Forward Indexes. WWW Jurek Leonhardt, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand
2022	J	`jnl`	MuCoMiD: A Multitask Graph Convolutional Learning Framework for miRNA-Disease Association Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. Ngan Dong, Stefanie Mücke, Megha Khosla
2022	J	`jnl`	Privacy and Transparency in Graph Machine Learning: A Unified Perspective. CoRR Megha Khosla
2022	J	`jnl`	Private Graph Extraction via Feature Explanations. CoRR Iyiola E. Olatunji, Mandeep Rathee, Thorben Funke, Megha Khosla
2021	J	`jnl`	A Comparative Study for Unsupervised Network Representation Learning. IEEE Trans. Knowl. Data Eng. Megha Khosla, Vinay Setty, Avishek Anand
2021	J	`jnl`	A Review of Anonymization for Healthcare Data. CoRR Iyiola E. Olatunji, Jens Rauch, Matthias Katzensteiner, Megha Khosla
2021	J	`jnl`	A multitask transfer learning framework for the prediction of virus-human protein-protein interactions. BMC Bioinform. Thi Ngan Dong, Graham Brogden, Gisa Gerold, Megha Khosla
2021	J	`jnl`	A multitask transfer learning framework for the prediction of virus-human protein-protein interactions. CoRR Thi Ngan Dong, Graham Brogden, Gisa Gerold, Megha Khosla
2021	J	`jnl`	Achieving differential privacy for k-nearest neighbors based outlier detection by data partitioning. CoRR Jens Rauch, Iyiola E. Olatunji, Megha Khosla
2021	Misc	`conf`	Extracting per Query Valid Explanations for Blackbox Learning-to-Rank Models. ICTIR Jaspreet Singh, Megha Khosla, Zhenye Wang, Avishek Anand
2021	J	`jnl`	Fast Forward Indexes for Efficient Document Ranking. CoRR Jurek Leonhardt, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand
2021	A	`conf`	Knowledge-Aware Neural Networks for Medical Forum Question Classification. CIKM Soumyadeep Roy, Sudip Chakraborty, Aishik Mandal, Gunjan Balde, Prakhar Sharma, Anandhavelu Natarajan, Megha Khosla, Shamik Sural, Niloy Ganguly
2021	J	`jnl`	Knowledge-Aware Neural Networks for Medical Forum Question Classification. CoRR Soumyadeep Roy, Sudip Chakraborty, Aishik Mandal, Gunjan Balde, Prakhar Sharma, Anandhavelu Natarajan, Megha Khosla, Shamik Sural, Niloy Ganguly
2021	J	`jnl`	Learnt Sparsification for Interpretable Graph Neural Networks. CoRR Mandeep Rathee, Zijian Zhang, Thorben Funke, Megha Khosla, Avishek Anand
2021	—	`conf`	Membership Inference Attack on Graph Neural Networks. TPS-ISA Iyiola E. Olatunji, Wolfgang Nejdl, Megha Khosla
2021	J	`jnl`	Membership Inference Attack on Graph Neural Networks. CoRR Iyiola E. Olatunji, Wolfgang Nejdl, Megha Khosla
2021	J	`jnl`	MuCoMiD: A Multitask Convolutional Learning Framework for miRNA-Disease Association Prediction. CoRR Thi Ngan Dong, Megha Khosla
2021	J	`jnl`	Releasing Graph Neural Networks with Differential Privacy Guarantees. CoRR Iyiola E. Olatunji, Thorben Funke, Megha Khosla
2021	J	`jnl`	Revisiting the Auction Algorithm for Weighted Bipartite Perfect Matchings. CoRR Megha Khosla, Avishek Anand
2021	J	`jnl`	Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks. CoRR Thorben Funke, Megha Khosla, Mandeep Rathee, Avishek Anand
2020	—	`conf`	Boilerplate Removal using a Neural Sequence Labeling Model. WWW (Companion Volume) Jurek Leonhardt, Avishek Anand, Megha Khosla
2020	J	`jnl`	Boilerplate Removal using a Neural Sequence Labeling Model. CoRR Jurek Leonhardt, Avishek Anand, Megha Khosla
2020	J	`jnl`	Deep Reinforcement Learning with Graph-based State Representations. CoRR Vikram Waradpande, Daniel Kudenko, Megha Khosla
2020	C	`conf`	Revisiting Feature Selection with Data Complexity. BIBE Ngan Thi Dong, Megha Khosla
2020	—	`conf`	Towards a consistent evaluation of miRNA-disease association prediction models. BIBM Thi Ngan Dong, Megha Khosla
2020	J	`jnl`	Valid Explanations for Learning to Rank Models. CoRR Jaspreet Singh, Megha Khosla, Avishek Anand
2019	J	`jnl`	A Comprehensive Comparison of Unsupervised Network Representation Learning Methods. CoRR Megha Khosla, Avishek Anand, Vinay Setty
2019	J	`jnl`	A Faster Algorithm for Cuckoo Insertion and Bipartite Matching in Large Graphs. Algorithmica Megha Khosla, Avishek Anand
2019	A	`conf`	Asynchronous Training of Word Embeddings for Large Text Corpora. WSDM Avishek Anand, Megha Khosla, Jaspreet Singh, Jan-Hendrik Zab, Zijian Zhang
2019	J	`jnl`	Estimating PageRank deviations in crawled graphs. Appl. Netw. Sci. Helge Holzmann, Avishek Anand, Megha Khosla
2019	—	`conf`	Finding Interpretable Concept Spaces in Node Embeddings Using Knowledge Bases. PKDD/ECML Workshops (1) Maximilian Idahl, Megha Khosla, Avishek Anand
2019	J	`jnl`	Finding Interpretable Concept Spaces in Node Embeddings using Knowledge Bases. CoRR Maximilian Idahl, Megha Khosla, Avishek Anand
2019	—	`conf`	Node Representation Learning for Directed Graphs. ECML/PKDD (1) Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl, Avishek Anand
2018	J	`jnl`	Asynchronous Training of Word Embeddings for Large Text Corpora. CoRR Avishek Anand, Megha Khosla, Jaspreet Singh, Jan-Hendrik Zab, Zijian Zhang
2018	—	`conf`	Delusive PageRank in Incomplete Graphs. COMPLEX NETWORKS (1) Helge Holzmann, Avishek Anand, Megha Khosla
2018	J	`jnl`	Node Representation Learning for Directed Graphs. CoRR Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl, Avishek Anand
2018	—	`conf`	User Fairness in Recommender Systems. WWW (Companion Volume) Jurek Leonhardt, Avishek Anand, Megha Khosla
2018	J	`jnl`	User Fairness in Recommender Systems. CoRR Jurek Leonhardt, Avishek Anand, Megha Khosla
2016	J	`jnl`	A Faster Algorithm for Cuckoo Insertion and Bipartite Matching in Large Graphs. CoRR Megha Khosla, Avishek Anand
2016	J	`jnl`	The Multiple-Orientability Thresholds for Random Hypergraphs. Comb. Probab. Comput. Nikolaos Fountoulakis, Megha Khosla, Konstantinos Panagiotou
2014	—	`—`	Multiple choice allocations with small maximum loads. Megha Khosla
2013	A	`conf`	Balls into Bins Made Faster. ESA Megha Khosla
2013	J	`jnl`	The Multiple-orientability Thresholds for Random Hypergraphs. CoRR Nikolaos Fountoulakis, Megha Khosla, Konstantinos Panagiotou
2011	A*	`conf`	The Multiple-Orientability Thresholds for Random Hypergraphs. SODA Nikolaos Fountoulakis, Megha Khosla, Konstantinos Panagiotou