Vankadara, Leena Chennuru

11 publications

NeurIPS 2025 On the Surprising Effectiveness of Large Learning Rates Under Standard Width Scaling Moritz Haas, Sebastian Bordt, Ulrike von Luxburg, Leena Chennuru Vankadara

NeurIPS 2024 $\boldsymbol{\mu}\mathbf{P^2}$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling Moritz Haas, Jin Xu, Volkan Cevher, Leena Chennuru Vankadara

ICMLW 2024 Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling Moritz Haas, Jin Xu, Volkan Cevher, Leena Chennuru Vankadara

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

NeurIPS 2024 On Feature Learning in Structured State Space Models Leena Chennuru Vankadara, Jin Xu, Moritz Haas, Volkan Cevher

JMLR 2023 Insights into Ordinal Embedding Algorithms: A Systematic Evaluation Leena Chennuru Vankadara, Michael Lohaus, Siavash Haghiri, Faiz Ul Wahab, Ulrike von Luxburg

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

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

NeurIPS 2018 Measures of Distortion for Machine Learning Leena Chennuru Vankadara, Ulrike von Luxburg