| 2026 | AsiaCCS | ALPHA: Active Learning with PAC-Bayesian Theory for Android Malware Detection. | Yaomengxi Han, Yunru Wang, Debarghya Ghoshdastidar, Johannes Kinder |
| 2025 | AAAI | When Can We Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis? | Gautham Govind Anil, Pascal Mattia Esser, Debarghya Ghoshdastidar |
| 2025 | AISTATS | Infinite Width Limits of Self Supervised Neural Networks. | Maximilian Fleissner, Gautham Govind Anil, Debarghya Ghoshdastidar |
| 2025 | ICLR | Exact Certification of (Graph) Neural Networks Against Label Poisoning. | Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Gnnemann, Debarghya Ghoshdastidar |
| 2024 | AAAI | Non-parametric Representation Learning with Kernels. | Pascal Mattia Esser, Maximilian Fleissner, Debarghya Ghoshdastidar |
| 2024 | ICLR | Explaining Kernel Clustering via Decision Trees. | Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar |
| 2023 | AISTATS | Improved Representation Learning Through Tensorized Autoencoders. | Pascal Mattia Esser, Satyaki Mukherjee, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar |
| 2022 | ICLR | Graphon based Clustering and Testing of Networks: Algorithms and Theory. | Mahalakshmi Sabanayagam, Leena Chennuru Vankadara, Debarghya Ghoshdastidar |
| 2022 | UAI | Causal forecasting: generalization bounds for autoregressive models. | Leena Chennuru Vankadara, Philipp Michael Faller, Michaela Hardt, Lenon Minorics, Debarghya Ghoshdastidar, Dominik Janzing |
| 2021 | AISTATS | Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models. | Leena C. Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar |
| 2020 | AISTATS | On the optimality of kernels for high-dimensional clustering. | Leena Chennuru Vankadara, Debarghya Ghoshdastidar |
| 2017 | AISTATS | Comparison-Based Nearest Neighbor Search. | Siavash Haghiri, Debarghya Ghoshdastidar, Ulrike von Luxburg |
| 2017 | COLT | Two-Sample Tests for Large Random Graphs Using Network Statistics. | Debarghya Ghoshdastidar, Maurilio Gutzeit, Alexandra Carpentier, Ulrike von Luxburg |
| 2016 | IJCNN | Mixture modeling with compact support distributions for unsupervised learning. | Ambedkar Dukkipati, Debarghya Ghoshdastidar, Jinu Krishnan |
| 2015 | AAAI | Spectral Clustering Using Multilinear SVD: Analysis, Approximations and Applications. | Debarghya Ghoshdastidar, Ambedkar Dukkipati |
| 2015 | ICML | A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning. | Debarghya Ghoshdastidar, Ambedkar Dukkipati |
| 2014 | CVPR | Spectral Clustering with Jensen-Type Kernels and Their Multi-point Extensions. | Debarghya Ghoshdastidar, Ambedkar Dukkipati, Ajay P. Adsul, Aparna S. Vijayan |
| 2013 | AAAI | On Power-Law Kernels, Corresponding Reproducing Kernel Hilbert Space and Applications. | Debarghya Ghoshdastidar, Ambedkar Dukkipati |
| 2013 | ICDM | Generative Maximum Entropy Learning for Multiclass Classification. | Ambedkar Dukkipati, Gaurav Pandey, Debarghya Ghoshdastidar, Paramita Koley, D. M. V. Satya Sriram |
| 2012 | ISIT | q-Gaussian based Smoothed Functional algorithms for stochastic optimization. | Debarghya Ghoshdastidar, Ambedkar Dukkipati, Shalabh Bhatnagar |