Ghoshdastidar, Debarghya

31 publications

ICLR 2025 Exact Certification of (Graph) Neural Networks Against Label Poisoning Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann, Debarghya Ghoshdastidar

ICLRW 2025 Exact Certification of (Graph) Neural Networks Against Label Poisoning Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann, Debarghya Ghoshdastidar

AISTATS 2025 Infinite Width Limits of Self Supervised Neural Networks Maximilian Fleissner, Gautham Govind Anil, Debarghya Ghoshdastidar

NeurIPS 2025 Non-Singularity of the Gradient Descent mAP for Neural Networks with Piecewise Analytic Activations Alexandru Crăciun, Debarghya Ghoshdastidar

TMLR 2025 Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks Lukas Gosch, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar, Stephan Günnemann

AAAI 2025 When Can We Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis? Gautham Govind Anil, Pascal Mattia Esser, Debarghya Ghoshdastidar

ICLR 2024 Explaining Kernel Clustering via Decision Trees Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar

AAAI 2024 Non-Parametric Representation Learning with Kernels Pascal Mattia Esser, Maximilian Fleissner, Debarghya Ghoshdastidar

NeurIPSW 2024 Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks Lukas Gosch, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar, Stephan Günnemann

TMLR 2024 Representation Learning Dynamics of Self-Supervised Models Pascal Esser, Satyaki Mukherjee, Debarghya Ghoshdastidar

TMLR 2024 Robust Feature Inference: A Test-Time Defense Strategy Using Spectral Projections Anurag Singh, Mahalakshmi Sabanayagam, Krikamol Muandet, Debarghya Ghoshdastidar

TMLR 2023 A Revenue Function for Comparison-Based Hierarchical Clustering Aishik Mandal, Michaël Perrot, Debarghya Ghoshdastidar

TMLR 2023 Analysis of Convolutions, Non-Linearity and Depth in Graph Neural Networks Using Neural Tangent Kernel Mahalakshmi Sabanayagam, Pascal Esser, Debarghya Ghoshdastidar

AISTATS 2023 Improved Representation Learning Through Tensorized Autoencoders Pascal Esser, Satyaki Mukherjee, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar

UAI 2022 Causal Forecasting: Generalization Bounds for Autoregressive Models Leena Chennuru Vankadara, Philipp Michael Faller, Michaela Hardt, Lenon Minorics, Debarghya Ghoshdastidar, Dominik Janzing

ICLR 2022 Graphon Based Clustering and Testing of Networks: Algorithms and Theory Mahalakshmi Sabanayagam, Leena Chennuru Vankadara, Debarghya Ghoshdastidar

NeurIPS 2022 Interpolation and Regularization for Causal Learning Leena Chennuru Vankadara, Luca Rendsburg, Ulrike V. Luxburg, Debarghya Ghoshdastidar

AISTATS 2021 Recovery Guarantees for Kernel-Based Clustering Under Non-Parametric Mixture Models Leena C. Vankadara, Sebastian Bordt, Ulrike Luxburg, Debarghya Ghoshdastidar

NeurIPS 2021 Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks Pascal Esser, Leena Chennuru Vankadara, Debarghya Ghoshdastidar

NeurIPS 2020 Near-Optimal Comparison Based Clustering Michaël Perrot, Pascal Esser, Debarghya Ghoshdastidar

AISTATS 2020 On the Optimality of Kernels for High-Dimensional Clustering Leena C Vankadara, Debarghya Ghoshdastidar

NeurIPS 2019 Foundations of Comparison-Based Hierarchical Clustering Debarghya Ghoshdastidar, Michaël Perrot, Ulrike von Luxburg

NeurIPS 2018 Practical Methods for Graph Two-Sample Testing Debarghya Ghoshdastidar, Ulrike von Luxburg

AISTATS 2017 Comparison-Based Nearest Neighbor Search Siavash Haghiri, Debarghya Ghoshdastidar, Ulrike von Luxburg

COLT 2017 Two-Sample Tests for Large Random Graphs Using Network Statistics Debarghya Ghoshdastidar, Maurilio Gutzeit, Alexandra Carpentier, Ulrike Luxburg

JMLR 2017 Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques Debarghya Ghoshdastidar, Ambedkar Dukkipati

ICML 2015 A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning Debarghya Ghoshdastidar, Ambedkar Dukkipati

AAAI 2015 Spectral Clustering Using Multilinear SVD: Analysis, Approximations and Applications Debarghya Ghoshdastidar, Ambedkar Dukkipati

NeurIPS 2014 Consistency of Spectral Partitioning of Uniform Hypergraphs Under Planted Partition Model Debarghya Ghoshdastidar, Ambedkar Dukkipati

CVPR 2014 Spectral Clustering with Jensen-Type Kernels and Their Multi-Point Extensions Debarghya Ghoshdastidar, Ambedkar Dukkipati, Ajay P. Adsul, Aparna S. Vijayan

AAAI 2013 On Power-Law Kernels, Corresponding Reproducing Kernel Hilbert Space and Applications Debarghya Ghoshdastidar, Ambedkar Dukkipati