← Authors

Debarghya Ghoshdastidar

21 papers · 2014–2025 · 9 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (11) 🐝 Cross-Pollinator (9) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (33) 🧭 Keyword Pioneer πŸ† Grand Slam πŸ† Keyword Champion (2) πŸ’Ž Century Club (21) πŸ”₯ Unstoppable (9) πŸ—ƒοΈ Keyword Collector (76) πŸ“ˆ Trend Setter ❓ The Questioner

Conferences

NIPS (6) AISTATS (5) ICLR (3) AAAI (2) COLT (1) CVPR (1) ICML (1) JMLR (1) UAI (1)

Top co-authors

Pascal Esser (5) Ulrike Von Luxburg (5) Leena Chennuru Vankadara (5) Ambedkar Dukkipati (4) Mahalakshmi Sabanayagam (3) Maximilian Fleissner (3) Gautham Govind Anil (2) MichaΓ«l Perrot (2) Maurilio Gutzeit (1) Philipp Michael Faller (1)

Keywords

spectral clustering (3) kernel methods (3) representation learning (3) tensor decomposition (3) principal component analysis (2) hypergraph partitioning (2) comparison-based learning (2) tensor method (2) contrastive learning (2) statistical inference (1) self-supervised learning (1) graph analysis (1) ridge regression (1) hierarchical clustering (1) image segmentation (1) learning theory (1) transductive learning (1) two-sample test (1) computer vision (1) statistical testing (1)

Papers

When Can We Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis? AAAI 2025
Infinite Width Limits of Self Supervised Neural Networks AISTATS 2025
Exact Certification of (Graph) Neural Networks Against Label Poisoning ICLR 2025
Non-parametric Representation Learning with Kernels AAAI 2024
Explaining Kernel Clustering via Decision Trees ICLR 2024
Improved Representation Learning Through Tensorized Autoencoders AISTATS 2023
Graphon based Clustering and Testing of Networks: Algorithms and Theory ICLR 2022
Causal forecasting: generalization bounds for autoregressive models UAI 2022
Interpolation and Regularization for Causal Learning NIPS 2022
Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models AISTATS 2021
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks NIPS 2021
Near-Optimal Comparison Based Clustering NIPS 2020
On the optimality of kernels for high-dimensional clustering AISTATS 2020
Foundations of Comparison-Based Hierarchical Clustering NIPS 2019
Practical Methods for Graph Two-Sample Testing NIPS 2018
Comparison-Based Nearest Neighbor Search AISTATS 2017
Two-Sample Tests for Large Random Graphs Using Network Statistics COLT 2017
Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques JMLR 2017
A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning ICML 2015
Spectral Clustering with Jensen-type Kernels and their Multi-point Extensions CVPR 2014
Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition Model NIPS 2014